Overview

Dataset statistics

Number of variables62
Number of observations167
Missing cells3995
Missing cells (%)38.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory81.0 KiB
Average record size in memory496.8 B

Variable types

Numeric13
Categorical40
Unsupported9

Alerts

airdate has constant value "2020-12-11" Constant
_embedded.show.dvdCountry.name has constant value "Russian Federation" Constant
_embedded.show.dvdCountry.code has constant value "RU" Constant
_embedded.show.dvdCountry.timezone has constant value "Asia/Kamchatka" Constant
url has a high cardinality: 167 distinct values High cardinality
name has a high cardinality: 153 distinct values High cardinality
summary has a high cardinality: 51 distinct values High cardinality
_links.self.href has a high cardinality: 167 distinct values High cardinality
_embedded.show.url has a high cardinality: 87 distinct values High cardinality
_embedded.show.name has a high cardinality: 87 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 67 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 78 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 82 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 82 distinct values High cardinality
_embedded.show.summary has a high cardinality: 77 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 87 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 87 distinct values High cardinality
image.medium has a high cardinality: 71 distinct values High cardinality
image.original has a high cardinality: 71 distinct values High cardinality
id is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
season is highly correlated with _embedded.show.externals.tvrage and 2 other fieldsHigh correlation
number is highly correlated with _embedded.show.externals.tvrageHigh correlation
runtime is highly correlated with _embedded.show.runtime and 2 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 6 other fieldsHigh correlation
id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
season is highly correlated with number and 5 other fieldsHigh correlation
number is highly correlated with season and 2 other fieldsHigh correlation
runtime is highly correlated with season and 3 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.weight and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.network.idHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with number and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 6 other fieldsHigh correlation
id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
season is highly correlated with _embedded.show.externals.tvrageHigh correlation
number is highly correlated with _embedded.show.externals.tvrageHigh correlation
runtime is highly correlated with _embedded.show.runtime and 2 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.externals.tvrageHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 2 other fieldsHigh correlation
id is highly correlated with type and 30 other fieldsHigh correlation
season is highly correlated with number and 27 other fieldsHigh correlation
number is highly correlated with season and 33 other fieldsHigh correlation
type is highly correlated with id and 17 other fieldsHigh correlation
airtime is highly correlated with season and 38 other fieldsHigh correlation
airstamp is highly correlated with id and 41 other fieldsHigh correlation
runtime is highly correlated with season and 41 other fieldsHigh correlation
summary is highly correlated with id and 36 other fieldsHigh correlation
rating.average is highly correlated with runtime and 24 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.status is highly correlated with airstamp and 34 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 35 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with season and 40 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 28 other fieldsHigh correlation
image.medium is highly correlated with id and 42 other fieldsHigh correlation
image.original is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with number and 33 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with number and 33 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with number and 33 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with number and 33 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with number and 33 other fieldsHigh correlation
number has 4 (2.4%) missing values Missing
runtime has 14 (8.4%) missing values Missing
image has 167 (100.0%) missing values Missing
summary has 116 (69.5%) missing values Missing
rating.average has 142 (85.0%) missing values Missing
_embedded.show.runtime has 47 (28.1%) missing values Missing
_embedded.show.averageRuntime has 11 (6.6%) missing values Missing
_embedded.show.ended has 77 (46.1%) missing values Missing
_embedded.show.officialSite has 18 (10.8%) missing values Missing
_embedded.show.rating.average has 141 (84.4%) missing values Missing
_embedded.show.network has 167 (100.0%) missing values Missing
_embedded.show.webChannel.id has 2 (1.2%) missing values Missing
_embedded.show.webChannel.name has 2 (1.2%) missing values Missing
_embedded.show.webChannel.country.name has 74 (44.3%) missing values Missing
_embedded.show.webChannel.country.code has 74 (44.3%) missing values Missing
_embedded.show.webChannel.country.timezone has 74 (44.3%) missing values Missing
_embedded.show.webChannel.officialSite has 83 (49.7%) missing values Missing
_embedded.show.dvdCountry has 167 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 164 (98.2%) missing values Missing
_embedded.show.externals.thetvdb has 34 (20.4%) missing values Missing
_embedded.show.externals.imdb has 59 (35.3%) missing values Missing
_embedded.show.image.medium has 5 (3.0%) missing values Missing
_embedded.show.image.original has 5 (3.0%) missing values Missing
_embedded.show.summary has 17 (10.2%) missing values Missing
_embedded.show._links.nextepisode.href has 162 (97.0%) missing values Missing
image.medium has 96 (57.5%) missing values Missing
image.original has 96 (57.5%) missing values Missing
_embedded.show.webChannel.country has 167 (100.0%) missing values Missing
_embedded.show.network.id has 162 (97.0%) missing values Missing
_embedded.show.network.name has 162 (97.0%) missing values Missing
_embedded.show.network.country.name has 162 (97.0%) missing values Missing
_embedded.show.network.country.code has 162 (97.0%) missing values Missing
_embedded.show.network.country.timezone has 162 (97.0%) missing values Missing
_embedded.show.network.officialSite has 167 (100.0%) missing values Missing
_embedded.show.webChannel has 167 (100.0%) missing values Missing
_embedded.show.image has 167 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 166 (99.4%) missing values Missing
_embedded.show.dvdCountry.code has 166 (99.4%) missing values Missing
_embedded.show.dvdCountry.timezone has 166 (99.4%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-05 04:37:18.380809
Analysis finished2022-09-05 04:37:51.432285
Duration33.05 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct167
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2022530.228
Minimum1910447
Maximum2341525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:51.506134image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1910447
5-th percentile1961339.7
Q11978329
median1986082
Q32030051.5
95-th percentile2300439.7
Maximum2341525
Range431078
Interquartile range (IQR)51722.5

Descriptive statistics

Standard deviation92811.49477
Coefficient of variation (CV)0.04588880478
Kurtosis4.141942285
Mean2022530.228
Median Absolute Deviation (MAD)11263
Skewness2.262800659
Sum337762548
Variance8613973562
MonotonicityNot monotonic
2022-09-04T23:37:51.686353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19681131
 
0.6%
19840841
 
0.6%
20374151
 
0.6%
19793081
 
0.6%
19794411
 
0.6%
19748191
 
0.6%
19748201
 
0.6%
19760941
 
0.6%
19760951
 
0.6%
19778701
 
0.6%
Other values (157)157
94.0%
ValueCountFrequency (%)
19104471
0.6%
19248891
0.6%
19400391
0.6%
19400401
0.6%
19452621
0.6%
19496351
0.6%
19517401
0.6%
19589661
0.6%
19610041
0.6%
19621231
0.6%
ValueCountFrequency (%)
23415251
0.6%
23361341
0.6%
23004461
0.6%
23004451
0.6%
23004441
0.6%
23004431
0.6%
23004421
0.6%
23004411
0.6%
23004401
0.6%
23004391
0.6%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct167
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
https://www.tvmaze.com/episodes/1968113/po-sezonu-videodajdzest-seasonvar-6x50-vypusk-304
 
1
https://www.tvmaze.com/episodes/1984084/el-desorden-que-dejas-1x07-la-tercera-victima
 
1
https://www.tvmaze.com/episodes/2037415/sobrevolando-1x05-peru-costa-do-pacifico
 
1
https://www.tvmaze.com/episodes/1979308/fjols-til-fjells-1x04-a-selge-de-baera-man-har
 
1
https://www.tvmaze.com/episodes/1979441/influencers-1x04-bound-to-happen
 
1
Other values (162)
162 

Length

Max length174
Median length101
Mean length80.31736527
Min length58

Characters and Unicode

Total characters13413
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1968113/po-sezonu-videodajdzest-seasonvar-6x50-vypusk-304
2nd rowhttps://www.tvmaze.com/episodes/1961004/cuma-2x07-seria-13
3rd rowhttps://www.tvmaze.com/episodes/1976572/zakon-i-besporyadok-1x05-seria-5
4th rowhttps://www.tvmaze.com/episodes/1986873/kotiki-1x10-seria-10
5th rowhttps://www.tvmaze.com/episodes/2030151/fox-spirit-matchmaker-9x01-episode-122

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1968113/po-sezonu-videodajdzest-seasonvar-6x50-vypusk-3041
 
0.6%
https://www.tvmaze.com/episodes/1984084/el-desorden-que-dejas-1x07-la-tercera-victima1
 
0.6%
https://www.tvmaze.com/episodes/2037415/sobrevolando-1x05-peru-costa-do-pacifico1
 
0.6%
https://www.tvmaze.com/episodes/1979308/fjols-til-fjells-1x04-a-selge-de-baera-man-har1
 
0.6%
https://www.tvmaze.com/episodes/1979441/influencers-1x04-bound-to-happen1
 
0.6%
https://www.tvmaze.com/episodes/1974819/wish-you-1x03-episode-31
 
0.6%
https://www.tvmaze.com/episodes/1974820/wish-you-1x04-episode-41
 
0.6%
https://www.tvmaze.com/episodes/1976094/be-with-you-1x21-episode-211
 
0.6%
https://www.tvmaze.com/episodes/1976095/be-with-you-1x22-episode-221
 
0.6%
https://www.tvmaze.com/episodes/1977870/a-generala-1x04-episodio-41
 
0.6%
Other values (157)157
94.0%

Length

2022-09-04T23:37:51.812355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1968113/po-sezonu-videodajdzest-seasonvar-6x50-vypusk-3041
 
0.6%
https://www.tvmaze.com/episodes/1965923/new-japan-pro-wrestling-2020-12-11-world-tag-league-2020best-of-the-super-jr27-finals1
 
0.6%
https://www.tvmaze.com/episodes/1976572/zakon-i-besporyadok-1x05-seria-51
 
0.6%
https://www.tvmaze.com/episodes/1986873/kotiki-1x10-seria-101
 
0.6%
https://www.tvmaze.com/episodes/2030151/fox-spirit-matchmaker-9x01-episode-1221
 
0.6%
https://www.tvmaze.com/episodes/2030152/fox-spirit-matchmaker-9x02-episode-1231
 
0.6%
https://www.tvmaze.com/episodes/1972563/the-wolf-1x21-episode-211
 
0.6%
https://www.tvmaze.com/episodes/1972564/the-wolf-1x22-episode-221
 
0.6%
https://www.tvmaze.com/episodes/1910447/the-founder-of-diabolism-q-1x21-a-tutorial1
 
0.6%
https://www.tvmaze.com/episodes/1998576/mr-right-is-here-1x05-episode-51
 
0.6%
Other values (157)157
94.0%

Most occurring characters

ValueCountFrequency (%)
e1214
 
9.1%
-1006
 
7.5%
s873
 
6.5%
/835
 
6.2%
t822
 
6.1%
o652
 
4.9%
a580
 
4.3%
w572
 
4.3%
i537
 
4.0%
m476
 
3.5%
Other values (30)5846
43.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter9245
68.9%
Decimal Number1826
 
13.6%
Other Punctuation1336
 
10.0%
Dash Punctuation1006
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1214
13.1%
s873
 
9.4%
t822
 
8.9%
o652
 
7.1%
a580
 
6.3%
w572
 
6.2%
i537
 
5.8%
m476
 
5.1%
p448
 
4.8%
d422
 
4.6%
Other values (16)2649
28.7%
Decimal Number
ValueCountFrequency (%)
1390
21.4%
0294
16.1%
2243
13.3%
9211
11.6%
8141
 
7.7%
5123
 
6.7%
4123
 
6.7%
3107
 
5.9%
797
 
5.3%
697
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/835
62.5%
.334
 
25.0%
:167
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-1006
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9245
68.9%
Common4168
31.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1214
13.1%
s873
 
9.4%
t822
 
8.9%
o652
 
7.1%
a580
 
6.3%
w572
 
6.2%
i537
 
5.8%
m476
 
5.1%
p448
 
4.8%
d422
 
4.6%
Other values (16)2649
28.7%
Common
ValueCountFrequency (%)
-1006
24.1%
/835
20.0%
1390
 
9.4%
.334
 
8.0%
0294
 
7.1%
2243
 
5.8%
9211
 
5.1%
:167
 
4.0%
8141
 
3.4%
5123
 
3.0%
Other values (4)424
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII13413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e1214
 
9.1%
-1006
 
7.5%
s873
 
6.5%
/835
 
6.2%
t822
 
6.1%
o652
 
4.9%
a580
 
4.3%
w572
 
4.3%
i537
 
4.0%
m476
 
3.5%
Other values (30)5846
43.6%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct153
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Episode 2
 
4
Episode 4
 
3
Episode 1
 
2
Episode 9
 
2
Episode 21
 
2
Other values (148)
154 

Length

Max length99
Median length43
Mean length17.4251497
Min length4

Characters and Unicode

Total characters2910
Distinct characters117
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)85.0%

Sample

1st rowВыпуск 304
2nd rowСерия 13
3rd rowСерия 5
4th rowСерия 10
5th rowEpisode 122

Common Values

ValueCountFrequency (%)
Episode 24
 
2.4%
Episode 43
 
1.8%
Episode 12
 
1.2%
Episode 92
 
1.2%
Episode 212
 
1.2%
Episode 222
 
1.2%
Episode 102
 
1.2%
Episode 52
 
1.2%
Episode 62
 
1.2%
Episode 32
 
1.2%
Other values (143)144
86.2%

Length

2022-09-04T23:37:51.979584image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode33
 
6.5%
the19
 
3.8%
day12
 
2.4%
a8
 
1.6%
7
 
1.4%
16
 
1.2%
of6
 
1.2%
26
 
1.2%
114
 
0.8%
no4
 
0.8%
Other values (333)400
79.2%

Most occurring characters

ValueCountFrequency (%)
338
 
11.6%
e291
 
10.0%
a180
 
6.2%
i172
 
5.9%
o146
 
5.0%
s124
 
4.3%
r122
 
4.2%
t106
 
3.6%
n100
 
3.4%
d98
 
3.4%
Other values (107)1233
42.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1955
67.2%
Uppercase Letter440
 
15.1%
Space Separator338
 
11.6%
Decimal Number112
 
3.8%
Other Punctuation43
 
1.5%
Dash Punctuation17
 
0.6%
Other Letter2
 
0.1%
Close Punctuation1
 
< 0.1%
Open Punctuation1
 
< 0.1%
Math Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e291
14.9%
a180
 
9.2%
i172
 
8.8%
o146
 
7.5%
s124
 
6.3%
r122
 
6.2%
t106
 
5.4%
n100
 
5.1%
d98
 
5.0%
l90
 
4.6%
Other values (41)526
26.9%
Uppercase Letter
ValueCountFrequency (%)
E52
 
11.8%
T46
 
10.5%
S35
 
8.0%
D30
 
6.8%
G23
 
5.2%
M21
 
4.8%
C21
 
4.8%
F20
 
4.5%
H18
 
4.1%
A18
 
4.1%
Other values (29)156
35.5%
Decimal Number
ValueCountFrequency (%)
133
29.5%
233
29.5%
013
 
11.6%
57
 
6.2%
37
 
6.2%
66
 
5.4%
45
 
4.5%
83
 
2.7%
93
 
2.7%
72
 
1.8%
Other Punctuation
ValueCountFrequency (%)
/8
18.6%
.7
16.3%
,7
16.3%
:5
11.6%
#4
9.3%
!4
9.3%
?2
 
4.7%
'2
 
4.7%
"2
 
4.7%
&2
 
4.7%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
338
100.0%
Dash Punctuation
ValueCountFrequency (%)
-17
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Math Symbol
ValueCountFrequency (%)
|1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2308
79.3%
Common513
 
17.6%
Cyrillic87
 
3.0%
Han2
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e291
 
12.6%
a180
 
7.8%
i172
 
7.5%
o146
 
6.3%
s124
 
5.4%
r122
 
5.3%
t106
 
4.6%
n100
 
4.3%
d98
 
4.2%
l90
 
3.9%
Other values (46)879
38.1%
Cyrillic
ValueCountFrequency (%)
и8
 
9.2%
р6
 
6.9%
с6
 
6.9%
к6
 
6.9%
А5
 
5.7%
С5
 
5.7%
е5
 
5.7%
я5
 
5.7%
о4
 
4.6%
а3
 
3.4%
Other values (24)34
39.1%
Common
ValueCountFrequency (%)
338
65.9%
133
 
6.4%
233
 
6.4%
-17
 
3.3%
013
 
2.5%
/8
 
1.6%
57
 
1.4%
.7
 
1.4%
,7
 
1.4%
37
 
1.4%
Other values (15)43
 
8.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2811
96.6%
Cyrillic87
 
3.0%
None10
 
0.3%
CJK2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
338
 
12.0%
e291
 
10.4%
a180
 
6.4%
i172
 
6.1%
o146
 
5.2%
s124
 
4.4%
r122
 
4.3%
t106
 
3.8%
n100
 
3.6%
d98
 
3.5%
Other values (64)1134
40.3%
Cyrillic
ValueCountFrequency (%)
и8
 
9.2%
р6
 
6.9%
с6
 
6.9%
к6
 
6.9%
А5
 
5.7%
С5
 
5.7%
е5
 
5.7%
я5
 
5.7%
о4
 
4.6%
а3
 
3.4%
Other values (24)34
39.1%
None
ValueCountFrequency (%)
í3
30.0%
ø2
20.0%
Å1
 
10.0%
æ1
 
10.0%
ä1
 
10.0%
ö1
 
10.0%
ó1
 
10.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.5988024
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:52.137878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile15.6
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation432.2887542
Coefficient of variation (CV)4.384320536
Kurtosis16.44847759
Mean98.5988024
Median Absolute Deviation (MAD)0
Skewness4.27212877
Sum16466
Variance186873.567
MonotonicityNot monotonic
2022-09-04T23:37:52.254016image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1101
60.5%
234
 
20.4%
310
 
6.0%
20208
 
4.8%
45
 
3.0%
94
 
2.4%
102
 
1.2%
61
 
0.6%
71
 
0.6%
181
 
0.6%
ValueCountFrequency (%)
1101
60.5%
234
 
20.4%
310
 
6.0%
45
 
3.0%
61
 
0.6%
71
 
0.6%
94
 
2.4%
102
 
1.2%
181
 
0.6%
20208
 
4.8%
ValueCountFrequency (%)
20208
 
4.8%
181
 
0.6%
102
 
1.2%
94
 
2.4%
71
 
0.6%
61
 
0.6%
45
 
3.0%
310
 
6.0%
234
 
20.4%
1101
60.5%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct44
Distinct (%)27.0%
Missing4
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean19.49079755
Minimum1
Maximum338
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:52.384091image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.5
median6
Q314.5
95-th percentile63.8
Maximum338
Range337
Interquartile range (IQR)11

Descriptive statistics

Standard deviation46.95432087
Coefficient of variation (CV)2.409050772
Kurtosis28.42505143
Mean19.49079755
Median Absolute Deviation (MAD)4
Skewness5.1207412
Sum3177
Variance2204.708248
MonotonicityNot monotonic
2022-09-04T23:37:52.536335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
217
 
10.2%
515
 
9.0%
415
 
9.0%
612
 
7.2%
112
 
7.2%
712
 
7.2%
312
 
7.2%
88
 
4.8%
106
 
3.6%
124
 
2.4%
Other values (34)50
29.9%
ValueCountFrequency (%)
112
7.2%
217
10.2%
312
7.2%
415
9.0%
515
9.0%
612
7.2%
712
7.2%
88
4.8%
94
 
2.4%
106
 
3.6%
ValueCountFrequency (%)
3381
0.6%
3001
0.6%
2991
0.6%
1921
0.6%
1501
0.6%
1121
0.6%
861
0.6%
811
0.6%
641
0.6%
621
0.6%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
regular
163 
insignificant_special
 
2
significant_special
 
2

Length

Max length21
Median length7
Mean length7.311377246
Min length7

Characters and Unicode

Total characters1221
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular163
97.6%
insignificant_special2
 
1.2%
significant_special2
 
1.2%

Length

2022-09-04T23:37:52.728209image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:37:52.839135image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
regular163
97.6%
insignificant_special2
 
1.2%
significant_special2
 
1.2%

Most occurring characters

ValueCountFrequency (%)
r326
26.7%
a171
14.0%
e167
13.7%
g167
13.7%
l167
13.7%
u163
13.3%
i18
 
1.5%
n10
 
0.8%
s8
 
0.7%
c8
 
0.7%
Other values (4)16
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1217
99.7%
Connector Punctuation4
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r326
26.8%
a171
14.1%
e167
13.7%
g167
13.7%
l167
13.7%
u163
13.4%
i18
 
1.5%
n10
 
0.8%
s8
 
0.7%
c8
 
0.7%
Other values (3)12
 
1.0%
Connector Punctuation
ValueCountFrequency (%)
_4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1217
99.7%
Common4
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
r326
26.8%
a171
14.1%
e167
13.7%
g167
13.7%
l167
13.7%
u163
13.4%
i18
 
1.5%
n10
 
0.8%
s8
 
0.7%
c8
 
0.7%
Other values (3)12
 
1.0%
Common
ValueCountFrequency (%)
_4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r326
26.7%
a171
14.0%
e167
13.7%
g167
13.7%
l167
13.7%
u163
13.3%
i18
 
1.5%
n10
 
0.8%
s8
 
0.7%
c8
 
0.7%
Other values (4)16
 
1.3%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2020-12-11
167 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1670
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-11
2nd row2020-12-11
3rd row2020-12-11
4th row2020-12-11
5th row2020-12-11

Common Values

ValueCountFrequency (%)
2020-12-11167
100.0%

Length

2022-09-04T23:37:52.948249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:37:53.108254image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-11167
100.0%

Most occurring characters

ValueCountFrequency (%)
2501
30.0%
1501
30.0%
0334
20.0%
-334
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1336
80.0%
Dash Punctuation334
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2501
37.5%
1501
37.5%
0334
25.0%
Dash Punctuation
ValueCountFrequency (%)
-334
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2501
30.0%
1501
30.0%
0334
20.0%
-334
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2501
30.0%
1501
30.0%
0334
20.0%
-334
20.0%

airtime
Categorical

HIGH CORRELATION

Distinct14
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
109 
12:00
20 
20:00
14 
00:01
 
8
21:00
 
4
Other values (9)
12 

Length

Max length5
Median length0
Mean length1.736526946
Min length0

Characters and Unicode

Total characters290
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)3.6%

Sample

1st row
2nd row
3rd row12:00
4th row
5th row

Common Values

ValueCountFrequency (%)
109
65.3%
12:0020
 
12.0%
20:0014
 
8.4%
00:018
 
4.8%
21:004
 
2.4%
06:002
 
1.2%
18:002
 
1.2%
23:002
 
1.2%
19:001
 
0.6%
08:301
 
0.6%
Other values (4)4
 
2.4%

Length

2022-09-04T23:37:53.213250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
12:0020
34.5%
20:0014
24.1%
00:018
 
13.8%
21:004
 
6.9%
06:002
 
3.4%
18:002
 
3.4%
23:002
 
3.4%
19:001
 
1.7%
08:301
 
1.7%
08:451
 
1.7%
Other values (3)3
 
5.2%

Most occurring characters

ValueCountFrequency (%)
0140
48.3%
:58
20.0%
244
 
15.2%
135
 
12.1%
84
 
1.4%
33
 
1.0%
62
 
0.7%
42
 
0.7%
91
 
0.3%
51
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number232
80.0%
Other Punctuation58
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0140
60.3%
244
 
19.0%
135
 
15.1%
84
 
1.7%
33
 
1.3%
62
 
0.9%
42
 
0.9%
91
 
0.4%
51
 
0.4%
Other Punctuation
ValueCountFrequency (%)
:58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common290
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0140
48.3%
:58
20.0%
244
 
15.2%
135
 
12.1%
84
 
1.4%
33
 
1.0%
62
 
0.7%
42
 
0.7%
91
 
0.3%
51
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0140
48.3%
:58
20.0%
244
 
15.2%
135
 
12.1%
84
 
1.4%
33
 
1.0%
62
 
0.7%
42
 
0.7%
91
 
0.3%
51
 
0.3%

airstamp
Categorical

HIGH CORRELATION

Distinct18
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2020-12-11T12:00:00+00:00
73 
2020-12-11T06:30:00+00:00
25 
2020-12-11T11:00:00+00:00
13 
2020-12-11T04:00:00+00:00
10 
2020-12-11T17:00:00+00:00
10 
Other values (13)
36 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters4175
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)3.6%

Sample

1st row2020-12-11T00:00:00+00:00
2nd row2020-12-11T00:00:00+00:00
3rd row2020-12-11T00:00:00+00:00
4th row2020-12-11T00:00:00+00:00
5th row2020-12-11T04:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-11T12:00:00+00:0073
43.7%
2020-12-11T06:30:00+00:0025
 
15.0%
2020-12-11T11:00:00+00:0013
 
7.8%
2020-12-11T04:00:00+00:0010
 
6.0%
2020-12-11T17:00:00+00:0010
 
6.0%
2020-12-11T10:00:00+00:009
 
5.4%
2020-12-11T22:01:00+00:008
 
4.8%
2020-12-11T00:00:00+00:004
 
2.4%
2020-12-12T02:00:00+00:003
 
1.8%
2020-12-12T04:00:00+00:002
 
1.2%
Other values (8)10
 
6.0%

Length

2022-09-04T23:37:53.372250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-11t12:00:00+00:0073
43.7%
2020-12-11t06:30:00+00:0025
 
15.0%
2020-12-11t11:00:00+00:0013
 
7.8%
2020-12-11t04:00:00+00:0010
 
6.0%
2020-12-11t17:00:00+00:0010
 
6.0%
2020-12-11t10:00:00+00:009
 
5.4%
2020-12-11t22:01:00+00:008
 
4.8%
2020-12-11t00:00:00+00:004
 
2.4%
2020-12-12t02:00:00+00:003
 
1.8%
2020-12-11t05:00:00+00:002
 
1.2%
Other values (8)10
 
6.0%

Most occurring characters

ValueCountFrequency (%)
01695
40.6%
1625
 
15.0%
2601
 
14.4%
:501
 
12.0%
-334
 
8.0%
T167
 
4.0%
+167
 
4.0%
329
 
0.7%
625
 
0.6%
415
 
0.4%
Other values (3)16
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3006
72.0%
Other Punctuation501
 
12.0%
Dash Punctuation334
 
8.0%
Uppercase Letter167
 
4.0%
Math Symbol167
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01695
56.4%
1625
 
20.8%
2601
 
20.0%
329
 
1.0%
625
 
0.8%
415
 
0.5%
710
 
0.3%
54
 
0.1%
92
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:501
100.0%
Dash Punctuation
ValueCountFrequency (%)
-334
100.0%
Uppercase Letter
ValueCountFrequency (%)
T167
100.0%
Math Symbol
ValueCountFrequency (%)
+167
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common4008
96.0%
Latin167
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01695
42.3%
1625
 
15.6%
2601
 
15.0%
:501
 
12.5%
-334
 
8.3%
+167
 
4.2%
329
 
0.7%
625
 
0.6%
415
 
0.4%
710
 
0.2%
Other values (2)6
 
0.1%
Latin
ValueCountFrequency (%)
T167
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01695
40.6%
1625
 
15.0%
2601
 
14.4%
:501
 
12.0%
-334
 
8.0%
T167
 
4.0%
+167
 
4.0%
329
 
0.7%
625
 
0.6%
415
 
0.4%
Other values (3)16
 
0.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct47
Distinct (%)30.7%
Missing14
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean34.78431373
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:53.520409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8
Q118
median30
Q345
95-th percentile60.8
Maximum180
Range175
Interquartile range (IQR)27

Descriptive statistics

Standard deviation26.03589152
Coefficient of variation (CV)0.7484951902
Kurtosis8.526734785
Mean34.78431373
Median Absolute Deviation (MAD)15
Skewness2.422723248
Sum5322
Variance677.8676471
MonotonicityNot monotonic
2022-09-04T23:37:53.688378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
2020
 
12.0%
4518
 
10.8%
5012
 
7.2%
3011
 
6.6%
189
 
5.4%
237
 
4.2%
1206
 
3.6%
105
 
3.0%
85
 
3.0%
154
 
2.4%
Other values (37)56
33.5%
(Missing)14
 
8.4%
ValueCountFrequency (%)
52
 
1.2%
61
 
0.6%
71
 
0.6%
85
3.0%
92
 
1.2%
105
3.0%
112
 
1.2%
121
 
0.6%
131
 
0.6%
142
 
1.2%
ValueCountFrequency (%)
1801
 
0.6%
1206
3.6%
621
 
0.6%
602
 
1.2%
591
 
0.6%
582
 
1.2%
571
 
0.6%
561
 
0.6%
551
 
0.6%
521
 
0.6%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing167
Missing (%)100.0%
Memory size1.4 KiB

summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct51
Distinct (%)100.0%
Missing116
Missing (%)69.5%
Memory size1.4 KiB
<p>Randi has to swallow many camels to get the family to Harry's shop. Liam never gets peace of mind, and August tries to cut the umbilical cord.</p>
 
1
<p>Raquel prepares to start her new job as a literature teacher at a high school grappling with intense drama and tragedy.</p><p><br /> </p>
 
1
<p>After her privacy is violated and being threatened, Raquel attempts to command respect from her students. Roi opens up to Viruca in his essays.</p><p><br /> </p>
 
1
<p>A guilt-ridden Raquel must decide how to respond to the blackmail involving her upcoming exam. Iago starts to get to know Viruca outside of class.</p><p><br /> </p>
 
1
<p>Desperate to learn more about Viruca, Raquel dives deeper into the late teacher's life. In the past, Iago is devastated by a realization.</p><p><br /> </p>
 
1
Other values (46)
46 

Length

Max length609
Median length174
Mean length196.0784314
Min length61

Characters and Unicode

Total characters10000
Distinct characters75
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row<p>Randi has to swallow many camels to get the family to Harry's shop. Liam never gets peace of mind, and August tries to cut the umbilical cord.</p>
2nd row<p>The mysterious murder of a female student causes unrest in university circles. With a close suspect, a close associate and friend, Professor Dimitris Lainis hastens to unravel the mystery.</p>
3rd row<p>Investigations into the murder have begun. And while the new Deputy Chief is determined to change everything, a mysterious file reaches the hands of the Director of Police Laboratories.</p>
4th row<p>Continuing the search for the murdered student, the police take DNA and fingerprints from the professors and the university staff. The pressure peaks when a new corpse is discovered.</p>
5th row<p>The two victims have one thing in common: a tattoo on Medusa's head. Later, after his visit to the University, Lieutenant Sklavis finds a note with the name of a girl.</p>

Common Values

ValueCountFrequency (%)
<p>Randi has to swallow many camels to get the family to Harry's shop. Liam never gets peace of mind, and August tries to cut the umbilical cord.</p>1
 
0.6%
<p>Raquel prepares to start her new job as a literature teacher at a high school grappling with intense drama and tragedy.</p><p><br /> </p>1
 
0.6%
<p>After her privacy is violated and being threatened, Raquel attempts to command respect from her students. Roi opens up to Viruca in his essays.</p><p><br /> </p>1
 
0.6%
<p>A guilt-ridden Raquel must decide how to respond to the blackmail involving her upcoming exam. Iago starts to get to know Viruca outside of class.</p><p><br /> </p>1
 
0.6%
<p>Desperate to learn more about Viruca, Raquel dives deeper into the late teacher's life. In the past, Iago is devastated by a realization.</p><p><br /> </p>1
 
0.6%
<p>Raquel's fear of her students increases and she voices her concerns to Germán. Viruca struggles with how to resolve her parents' financial situation.</p><p><br /> </p>1
 
0.6%
<p>Raquel continues to unravel a dangerous web of lies as she tries to determine whether she can trust even those closest to her.</p><p><br /> </p>1
 
0.6%
<p>Roi decides to do some investigating of his own. Raquel starts turning to an unlikely source for comfort. Iago continues to seek attention from Viruca.</p><p><br /> </p>1
 
0.6%
<p>As Raquel gets closer to discovering the truth about Viruca's death, she puts herself in grave danger. Iago makes a torturous decision.</p>1
 
0.6%
<p>Sometimes, actions speak louder than words. #InfluencersEP4 will show how loud it is.</p>1
 
0.6%
Other values (41)41
 
24.6%
(Missing)116
69.5%

Length

2022-09-04T23:37:53.865181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the104
 
6.4%
to61
 
3.8%
and48
 
3.0%
a47
 
2.9%
of46
 
2.8%
in24
 
1.5%
her23
 
1.4%
is17
 
1.0%
that15
 
0.9%
their14
 
0.9%
Other values (814)1222
75.4%

Most occurring characters

ValueCountFrequency (%)
1557
15.6%
e944
 
9.4%
t714
 
7.1%
a660
 
6.6%
i588
 
5.9%
s569
 
5.7%
o520
 
5.2%
n493
 
4.9%
r486
 
4.9%
h410
 
4.1%
Other values (65)3059
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7551
75.5%
Space Separator1572
 
15.7%
Other Punctuation319
 
3.2%
Uppercase Letter267
 
2.7%
Math Symbol258
 
2.6%
Decimal Number17
 
0.2%
Dash Punctuation16
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e944
12.5%
t714
 
9.5%
a660
 
8.7%
i588
 
7.8%
s569
 
7.5%
o520
 
6.9%
n493
 
6.5%
r486
 
6.4%
h410
 
5.4%
l303
 
4.0%
Other values (17)1864
24.7%
Uppercase Letter
ValueCountFrequency (%)
A29
 
10.9%
M27
 
10.1%
T23
 
8.6%
S21
 
7.9%
R20
 
7.5%
I16
 
6.0%
L16
 
6.0%
C13
 
4.9%
F11
 
4.1%
W10
 
3.7%
Other values (15)81
30.3%
Other Punctuation
ValueCountFrequency (%)
.93
29.2%
,81
25.4%
/70
21.9%
'49
15.4%
"10
 
3.1%
:8
 
2.5%
!5
 
1.6%
#1
 
0.3%
;1
 
0.3%
?1
 
0.3%
Decimal Number
ValueCountFrequency (%)
15
29.4%
05
29.4%
22
 
11.8%
52
 
11.8%
91
 
5.9%
81
 
5.9%
41
 
5.9%
Space Separator
ValueCountFrequency (%)
1557
99.0%
 15
 
1.0%
Math Symbol
ValueCountFrequency (%)
>129
50.0%
<129
50.0%
Dash Punctuation
ValueCountFrequency (%)
-14
87.5%
2
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin7818
78.2%
Common2182
 
21.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e944
12.1%
t714
 
9.1%
a660
 
8.4%
i588
 
7.5%
s569
 
7.3%
o520
 
6.7%
n493
 
6.3%
r486
 
6.2%
h410
 
5.2%
l303
 
3.9%
Other values (42)2131
27.3%
Common
ValueCountFrequency (%)
1557
71.4%
>129
 
5.9%
<129
 
5.9%
.93
 
4.3%
,81
 
3.7%
/70
 
3.2%
'49
 
2.2%
 15
 
0.7%
-14
 
0.6%
"10
 
0.5%
Other values (13)35
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII9982
99.8%
None16
 
0.2%
Punctuation2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1557
15.6%
e944
 
9.5%
t714
 
7.2%
a660
 
6.6%
i588
 
5.9%
s569
 
5.7%
o520
 
5.2%
n493
 
4.9%
r486
 
4.9%
h410
 
4.1%
Other values (62)3041
30.5%
None
ValueCountFrequency (%)
 15
93.8%
á1
 
6.2%
Punctuation
ValueCountFrequency (%)
2
100.0%

rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct11
Distinct (%)44.0%
Missing142
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean7.68
Minimum5
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:54.016026image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6.8
Q17
median8
Q38.2
95-th percentile9
Maximum9
Range4
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation0.9224062735
Coefficient of variation (CV)0.1201049835
Kurtosis1.462911604
Mean7.68
Median Absolute Deviation (MAD)0.9
Skewness-0.7453302935
Sum192
Variance0.8508333333
MonotonicityNot monotonic
2022-09-04T23:37:54.103026image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
76
 
3.6%
8.13
 
1.8%
83
 
1.8%
93
 
1.8%
8.22
 
1.2%
7.32
 
1.2%
6.82
 
1.2%
8.41
 
0.6%
7.81
 
0.6%
8.91
 
0.6%
(Missing)142
85.0%
ValueCountFrequency (%)
51
 
0.6%
6.82
 
1.2%
76
3.6%
7.32
 
1.2%
7.81
 
0.6%
83
1.8%
8.13
1.8%
8.22
 
1.2%
8.41
 
0.6%
8.91
 
0.6%
ValueCountFrequency (%)
93
1.8%
8.91
 
0.6%
8.41
 
0.6%
8.22
 
1.2%
8.13
1.8%
83
1.8%
7.81
 
0.6%
7.32
 
1.2%
76
3.6%
6.82
 
1.2%

_links.self.href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct167
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
https://api.tvmaze.com/episodes/1968113
 
1
https://api.tvmaze.com/episodes/1984084
 
1
https://api.tvmaze.com/episodes/2037415
 
1
https://api.tvmaze.com/episodes/1979308
 
1
https://api.tvmaze.com/episodes/1979441
 
1
Other values (162)
162 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters6513
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1968113
2nd rowhttps://api.tvmaze.com/episodes/1961004
3rd rowhttps://api.tvmaze.com/episodes/1976572
4th rowhttps://api.tvmaze.com/episodes/1986873
5th rowhttps://api.tvmaze.com/episodes/2030151

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19681131
 
0.6%
https://api.tvmaze.com/episodes/19840841
 
0.6%
https://api.tvmaze.com/episodes/20374151
 
0.6%
https://api.tvmaze.com/episodes/19793081
 
0.6%
https://api.tvmaze.com/episodes/19794411
 
0.6%
https://api.tvmaze.com/episodes/19748191
 
0.6%
https://api.tvmaze.com/episodes/19748201
 
0.6%
https://api.tvmaze.com/episodes/19760941
 
0.6%
https://api.tvmaze.com/episodes/19760951
 
0.6%
https://api.tvmaze.com/episodes/19778701
 
0.6%
Other values (157)157
94.0%

Length

2022-09-04T23:37:54.251247image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19681131
 
0.6%
https://api.tvmaze.com/episodes/19659231
 
0.6%
https://api.tvmaze.com/episodes/19765721
 
0.6%
https://api.tvmaze.com/episodes/19868731
 
0.6%
https://api.tvmaze.com/episodes/20301511
 
0.6%
https://api.tvmaze.com/episodes/20301521
 
0.6%
https://api.tvmaze.com/episodes/19725631
 
0.6%
https://api.tvmaze.com/episodes/19725641
 
0.6%
https://api.tvmaze.com/episodes/19104471
 
0.6%
https://api.tvmaze.com/episodes/19985761
 
0.6%
Other values (157)157
94.0%

Most occurring characters

ValueCountFrequency (%)
/668
 
10.3%
p501
 
7.7%
s501
 
7.7%
e501
 
7.7%
t501
 
7.7%
o334
 
5.1%
a334
 
5.1%
i334
 
5.1%
.334
 
5.1%
m334
 
5.1%
Other values (16)2171
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4175
64.1%
Other Punctuation1169
 
17.9%
Decimal Number1169
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p501
12.0%
s501
12.0%
e501
12.0%
t501
12.0%
o334
8.0%
a334
8.0%
i334
8.0%
m334
8.0%
h167
 
4.0%
d167
 
4.0%
Other values (3)501
12.0%
Decimal Number
ValueCountFrequency (%)
9196
16.8%
1183
15.7%
0143
12.2%
8125
10.7%
2108
9.2%
494
8.0%
592
7.9%
781
6.9%
674
 
6.3%
373
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/668
57.1%
.334
28.6%
:167
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin4175
64.1%
Common2338
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/668
28.6%
.334
14.3%
9196
 
8.4%
1183
 
7.8%
:167
 
7.1%
0143
 
6.1%
8125
 
5.3%
2108
 
4.6%
494
 
4.0%
592
 
3.9%
Other values (3)228
 
9.8%
Latin
ValueCountFrequency (%)
p501
12.0%
s501
12.0%
e501
12.0%
t501
12.0%
o334
8.0%
a334
8.0%
i334
8.0%
m334
8.0%
h167
 
4.0%
d167
 
4.0%
Other values (3)501
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/668
 
10.3%
p501
 
7.7%
s501
 
7.7%
e501
 
7.7%
t501
 
7.7%
o334
 
5.1%
a334
 
5.1%
i334
 
5.1%
.334
 
5.1%
m334
 
5.1%
Other values (16)2171
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct87
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47867.7006
Minimum7847
Maximum62418
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:54.564418image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7847
5-th percentile22795.5
Q145987
median50467
Q352451
95-th percentile60427
Maximum62418
Range54571
Interquartile range (IQR)6464

Descriptive statistics

Standard deviation10414.24096
Coefficient of variation (CV)0.2175630087
Kurtosis4.395790673
Mean47867.7006
Median Absolute Deviation (MAD)2586
Skewness-2.003440996
Sum7993906
Variance108456414.8
MonotonicityNot monotonic
2022-09-04T23:37:54.734780image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5046716
 
9.6%
3739010
 
6.0%
543818
 
4.8%
516538
 
4.8%
459878
 
4.8%
604278
 
4.8%
478817
 
4.2%
497216
 
3.6%
524514
 
2.4%
234012
 
1.2%
Other values (77)90
53.9%
ValueCountFrequency (%)
78471
0.6%
80351
0.6%
115022
1.2%
152502
1.2%
207342
1.2%
225361
0.6%
234012
1.2%
249631
0.6%
306061
0.6%
368131
0.6%
ValueCountFrequency (%)
624181
 
0.6%
623061
 
0.6%
611401
 
0.6%
608091
 
0.6%
604278
4.8%
596761
 
0.6%
583671
 
0.6%
579531
 
0.6%
574911
 
0.6%
564331
 
0.6%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct87
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
https://www.tvmaze.com/shows/50467/bebaakee
16 
https://www.tvmaze.com/shows/37390/the-wilds
 
10
https://www.tvmaze.com/shows/54381/triples
 
8
https://www.tvmaze.com/shows/51653/el-desorden-que-dejas
 
8
https://www.tvmaze.com/shows/45987/eteros-ego-chamenes-psyches
 
8
Other values (82)
117 

Length

Max length77
Median length66
Mean length51.71856287
Min length39

Characters and Unicode

Total characters8637
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)38.3%

Sample

1st rowhttps://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvar
2nd rowhttps://www.tvmaze.com/shows/48402/cuma
3rd rowhttps://www.tvmaze.com/shows/52118/zakon-i-besporyadok
4th rowhttps://www.tvmaze.com/shows/52198/kotiki
5th rowhttps://www.tvmaze.com/shows/20734/fox-spirit-matchmaker

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/50467/bebaakee16
 
9.6%
https://www.tvmaze.com/shows/37390/the-wilds10
 
6.0%
https://www.tvmaze.com/shows/54381/triples8
 
4.8%
https://www.tvmaze.com/shows/51653/el-desorden-que-dejas8
 
4.8%
https://www.tvmaze.com/shows/45987/eteros-ego-chamenes-psyches8
 
4.8%
https://www.tvmaze.com/shows/60427/justimus-esittaa-duo8
 
4.8%
https://www.tvmaze.com/shows/47881/clifford-the-big-red-dog7
 
4.2%
https://www.tvmaze.com/shows/49721/madagascar-a-little-wild6
 
3.6%
https://www.tvmaze.com/shows/52451/the-burning-river4
 
2.4%
https://www.tvmaze.com/shows/23401/mickey-mouse-mixed-up-adventures2
 
1.2%
Other values (77)90
53.9%

Length

2022-09-04T23:37:54.887229image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/50467/bebaakee16
 
9.6%
https://www.tvmaze.com/shows/37390/the-wilds10
 
6.0%
https://www.tvmaze.com/shows/54381/triples8
 
4.8%
https://www.tvmaze.com/shows/51653/el-desorden-que-dejas8
 
4.8%
https://www.tvmaze.com/shows/45987/eteros-ego-chamenes-psyches8
 
4.8%
https://www.tvmaze.com/shows/60427/justimus-esittaa-duo8
 
4.8%
https://www.tvmaze.com/shows/47881/clifford-the-big-red-dog7
 
4.2%
https://www.tvmaze.com/shows/49721/madagascar-a-little-wild6
 
3.6%
https://www.tvmaze.com/shows/52451/the-burning-river4
 
2.4%
https://www.tvmaze.com/shows/52571/lassemajas-detektivbyra2
 
1.2%
Other values (77)90
53.9%

Most occurring characters

ValueCountFrequency (%)
/835
 
9.7%
w709
 
8.2%
s694
 
8.0%
t667
 
7.7%
e525
 
6.1%
o486
 
5.6%
h427
 
4.9%
m418
 
4.8%
a360
 
4.2%
.334
 
3.9%
Other values (30)3182
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6157
71.3%
Other Punctuation1336
 
15.5%
Decimal Number836
 
9.7%
Dash Punctuation308
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w709
11.5%
s694
11.3%
t667
10.8%
e525
 
8.5%
o486
 
7.9%
h427
 
6.9%
m418
 
6.8%
a360
 
5.8%
c231
 
3.8%
p203
 
3.3%
Other values (16)1437
23.3%
Decimal Number
ValueCountFrequency (%)
5146
17.5%
4108
12.9%
193
11.1%
081
9.7%
779
9.4%
276
9.1%
371
8.5%
667
8.0%
859
7.1%
956
 
6.7%
Other Punctuation
ValueCountFrequency (%)
/835
62.5%
.334
 
25.0%
:167
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-308
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6157
71.3%
Common2480
28.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
w709
11.5%
s694
11.3%
t667
10.8%
e525
 
8.5%
o486
 
7.9%
h427
 
6.9%
m418
 
6.8%
a360
 
5.8%
c231
 
3.8%
p203
 
3.3%
Other values (16)1437
23.3%
Common
ValueCountFrequency (%)
/835
33.7%
.334
 
13.5%
-308
 
12.4%
:167
 
6.7%
5146
 
5.9%
4108
 
4.4%
193
 
3.8%
081
 
3.3%
779
 
3.2%
276
 
3.1%
Other values (4)253
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII8637
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/835
 
9.7%
w709
 
8.2%
s694
 
8.0%
t667
 
7.7%
e525
 
6.1%
o486
 
5.6%
h427
 
4.9%
m418
 
4.8%
a360
 
4.2%
.334
 
3.9%
Other values (30)3182
36.8%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct87
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Bebaakee
16 
The Wilds
 
10
Triples
 
8
El desorden que dejas
 
8
Έτερος Εγώ: Χαμένες Ψυχές
 
8
Other values (82)
117 

Length

Max length44
Median length31
Mean length16.82035928
Min length5

Characters and Unicode

Total characters2809
Distinct characters110
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)38.3%

Sample

1st rowПо сезону. Видеодайджест Seasonvar
2nd rowЧума!
3rd rowZakon i Besporyadok
4th rowКотики
5th rowFox Spirit Matchmaker

Common Values

ValueCountFrequency (%)
Bebaakee16
 
9.6%
The Wilds10
 
6.0%
Triples8
 
4.8%
El desorden que dejas8
 
4.8%
Έτερος Εγώ: Χαμένες Ψυχές8
 
4.8%
Justimus esittää: Duo8
 
4.8%
Clifford the Big Red Dog7
 
4.2%
Madagascar: A Little Wild6
 
3.6%
The Burning River4
 
2.4%
Mickey Mouse: Mixed-Up Adventures2
 
1.2%
Other values (77)90
53.9%

Length

2022-09-04T23:37:55.082978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the37
 
7.9%
bebaakee16
 
3.4%
wilds10
 
2.1%
εγώ8
 
1.7%
red8
 
1.7%
triples8
 
1.7%
justimus8
 
1.7%
ψυχές8
 
1.7%
χαμένες8
 
1.7%
duo8
 
1.7%
Other values (204)350
74.6%

Most occurring characters

ValueCountFrequency (%)
302
 
10.8%
e293
 
10.4%
i163
 
5.8%
a147
 
5.2%
s140
 
5.0%
o123
 
4.4%
r118
 
4.2%
t113
 
4.0%
l91
 
3.2%
d90
 
3.2%
Other values (100)1229
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2043
72.7%
Uppercase Letter416
 
14.8%
Space Separator302
 
10.8%
Other Punctuation39
 
1.4%
Dash Punctuation6
 
0.2%
Decimal Number3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e293
14.3%
i163
 
8.0%
a147
 
7.2%
s140
 
6.9%
o123
 
6.0%
r118
 
5.8%
t113
 
5.5%
l91
 
4.5%
d90
 
4.4%
n87
 
4.3%
Other values (48)678
33.2%
Uppercase Letter
ValueCountFrequency (%)
T42
 
10.1%
B41
 
9.9%
M39
 
9.4%
D30
 
7.2%
W30
 
7.2%
L22
 
5.3%
R22
 
5.3%
S17
 
4.1%
C16
 
3.8%
J15
 
3.6%
Other values (32)142
34.1%
Other Punctuation
ValueCountFrequency (%)
:31
79.5%
.3
 
7.7%
!3
 
7.7%
'1
 
2.6%
,1
 
2.6%
Decimal Number
ValueCountFrequency (%)
51
33.3%
01
33.3%
21
33.3%
Space Separator
ValueCountFrequency (%)
302
100.0%
Dash Punctuation
ValueCountFrequency (%)
-6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2231
79.4%
Common350
 
12.5%
Greek168
 
6.0%
Cyrillic60
 
2.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e293
 
13.1%
i163
 
7.3%
a147
 
6.6%
s140
 
6.3%
o123
 
5.5%
r118
 
5.3%
t113
 
5.1%
l91
 
4.1%
d90
 
4.0%
n87
 
3.9%
Other values (45)866
38.8%
Cyrillic
ValueCountFrequency (%)
и6
 
10.0%
а5
 
8.3%
о5
 
8.3%
е5
 
8.3%
д5
 
8.3%
с4
 
6.7%
к3
 
5.0%
з2
 
3.3%
н2
 
3.3%
у2
 
3.3%
Other values (18)21
35.0%
Greek
ValueCountFrequency (%)
ς24
14.3%
ε16
 
9.5%
έ16
 
9.5%
χ8
 
4.8%
ο8
 
4.8%
Έ8
 
4.8%
τ8
 
4.8%
υ8
 
4.8%
ρ8
 
4.8%
Ε8
 
4.8%
Other values (7)56
33.3%
Common
ValueCountFrequency (%)
302
86.3%
:31
 
8.9%
-6
 
1.7%
.3
 
0.9%
!3
 
0.9%
'1
 
0.3%
51
 
0.3%
01
 
0.3%
21
 
0.3%
,1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2556
91.0%
None193
 
6.9%
Cyrillic60
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
302
 
11.8%
e293
 
11.5%
i163
 
6.4%
a147
 
5.8%
s140
 
5.5%
o123
 
4.8%
r118
 
4.6%
t113
 
4.4%
l91
 
3.6%
d90
 
3.5%
Other values (51)976
38.2%
None
ValueCountFrequency (%)
ς24
 
12.4%
ä17
 
8.8%
ε16
 
8.3%
έ16
 
8.3%
χ8
 
4.1%
ο8
 
4.1%
Έ8
 
4.1%
τ8
 
4.1%
υ8
 
4.1%
ρ8
 
4.1%
Other values (11)72
37.3%
Cyrillic
ValueCountFrequency (%)
и6
 
10.0%
а5
 
8.3%
о5
 
8.3%
е5
 
8.3%
д5
 
8.3%
с4
 
6.7%
к3
 
5.0%
з2
 
3.3%
н2
 
3.3%
у2
 
3.3%
Other values (18)21
35.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Scripted
103 
Animation
27 
Documentary
 
10
Reality
 
8
Talk Show
 
6
Other values (4)
13 

Length

Max length11
Median length8
Mean length8.203592814
Min length4

Characters and Unicode

Total characters1370
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st rowTalk Show
2nd rowScripted
3rd rowScripted
4th rowScripted
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted103
61.7%
Animation27
 
16.2%
Documentary10
 
6.0%
Reality8
 
4.8%
Talk Show6
 
3.6%
Variety6
 
3.6%
Sports4
 
2.4%
News2
 
1.2%
Game Show1
 
0.6%

Length

2022-09-04T23:37:55.226979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:37:55.442206image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted103
59.2%
animation27
 
15.5%
documentary10
 
5.7%
reality8
 
4.6%
show7
 
4.0%
talk6
 
3.4%
variety6
 
3.4%
sports4
 
2.3%
news2
 
1.1%
game1
 
0.6%

Most occurring characters

ValueCountFrequency (%)
i171
12.5%
t158
11.5%
e130
9.5%
r123
9.0%
S114
8.3%
c113
8.2%
p107
7.8%
d103
7.5%
n64
 
4.7%
a58
 
4.2%
Other values (17)229
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1189
86.8%
Uppercase Letter174
 
12.7%
Space Separator7
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i171
14.4%
t158
13.3%
e130
10.9%
r123
10.3%
c113
9.5%
p107
9.0%
d103
8.7%
n64
 
5.4%
a58
 
4.9%
o48
 
4.0%
Other values (8)114
9.6%
Uppercase Letter
ValueCountFrequency (%)
S114
65.5%
A27
 
15.5%
D10
 
5.7%
R8
 
4.6%
T6
 
3.4%
V6
 
3.4%
N2
 
1.1%
G1
 
0.6%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1363
99.5%
Common7
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i171
12.5%
t158
11.6%
e130
9.5%
r123
9.0%
S114
8.4%
c113
8.3%
p107
7.9%
d103
7.6%
n64
 
4.7%
a58
 
4.3%
Other values (16)222
16.3%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1370
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i171
12.5%
t158
11.5%
e130
9.5%
r123
9.0%
S114
8.3%
c113
8.2%
p107
7.8%
d103
7.5%
n64
 
4.7%
a58
 
4.2%
Other values (17)229
16.7%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct20
Distinct (%)12.0%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
English
51 
Chinese
22 
Hindi
17 
Spanish
11 
Norwegian
10 
Other values (15)
55 

Length

Max length10
Median length7
Mean length6.626506024
Min length4

Characters and Unicode

Total characters1100
Distinct characters34
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)3.0%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowChinese

Common Values

ValueCountFrequency (%)
English51
30.5%
Chinese22
13.2%
Hindi17
 
10.2%
Spanish11
 
6.6%
Norwegian10
 
6.0%
Korean9
 
5.4%
Greek8
 
4.8%
Finnish8
 
4.8%
Tamil8
 
4.8%
Russian6
 
3.6%
Other values (10)16
 
9.6%

Length

2022-09-04T23:37:55.581256image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english51
30.7%
chinese22
13.3%
hindi17
 
10.2%
spanish11
 
6.6%
norwegian10
 
6.0%
korean9
 
5.4%
greek8
 
4.8%
finnish8
 
4.8%
tamil8
 
4.8%
russian6
 
3.6%
Other values (10)16
 
9.6%

Most occurring characters

ValueCountFrequency (%)
i164
14.9%
n148
13.5%
s110
10.0%
h100
9.1%
e90
8.2%
g67
 
6.1%
l62
 
5.6%
a57
 
5.2%
E51
 
4.6%
r31
 
2.8%
Other values (24)220
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter934
84.9%
Uppercase Letter166
 
15.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i164
17.6%
n148
15.8%
s110
11.8%
h100
10.7%
e90
9.6%
g67
7.2%
l62
 
6.6%
a57
 
6.1%
r31
 
3.3%
o24
 
2.6%
Other values (9)81
8.7%
Uppercase Letter
ValueCountFrequency (%)
E51
30.7%
C22
13.3%
H17
 
10.2%
S13
 
7.8%
T13
 
7.8%
N10
 
6.0%
K9
 
5.4%
G9
 
5.4%
F9
 
5.4%
R6
 
3.6%
Other values (5)7
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Latin1100
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i164
14.9%
n148
13.5%
s110
10.0%
h100
9.1%
e90
8.2%
g67
 
6.1%
l62
 
5.6%
a57
 
5.2%
E51
 
4.6%
r31
 
2.8%
Other values (24)220
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i164
14.9%
n148
13.5%
s110
10.0%
h100
9.1%
e90
8.2%
g67
 
6.1%
l62
 
5.6%
a57
 
5.2%
E51
 
4.6%
r31
 
2.8%
Other values (24)220
20.0%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.4 KiB

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Ended
90 
Running
60 
To Be Determined
17 

Length

Max length16
Median length5
Mean length6.838323353
Min length5

Characters and Unicode

Total characters1142
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowEnded
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended90
53.9%
Running60
35.9%
To Be Determined17
 
10.2%

Length

2022-09-04T23:37:55.682292image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:37:55.834515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ended90
44.8%
running60
29.9%
to17
 
8.5%
be17
 
8.5%
determined17
 
8.5%

Most occurring characters

ValueCountFrequency (%)
n287
25.1%
d197
17.3%
e158
13.8%
E90
 
7.9%
i77
 
6.7%
R60
 
5.3%
u60
 
5.3%
g60
 
5.3%
34
 
3.0%
T17
 
1.5%
Other values (6)102
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter907
79.4%
Uppercase Letter201
 
17.6%
Space Separator34
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n287
31.6%
d197
21.7%
e158
17.4%
i77
 
8.5%
u60
 
6.6%
g60
 
6.6%
o17
 
1.9%
t17
 
1.9%
r17
 
1.9%
m17
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
E90
44.8%
R60
29.9%
T17
 
8.5%
B17
 
8.5%
D17
 
8.5%
Space Separator
ValueCountFrequency (%)
34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1108
97.0%
Common34
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n287
25.9%
d197
17.8%
e158
14.3%
E90
 
8.1%
i77
 
6.9%
R60
 
5.4%
u60
 
5.4%
g60
 
5.4%
T17
 
1.5%
o17
 
1.5%
Other values (5)85
 
7.7%
Common
ValueCountFrequency (%)
34
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1142
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n287
25.1%
d197
17.3%
e158
13.8%
E90
 
7.9%
i77
 
6.7%
R60
 
5.3%
u60
 
5.3%
g60
 
5.3%
34
 
3.0%
T17
 
1.5%
Other values (6)102
 
8.9%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct25
Distinct (%)20.8%
Missing47
Missing (%)28.1%
Infinite0
Infinite (%)0.0%
Mean35.34166667
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:55.933658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile9.95
Q118
median30
Q345
95-th percentile120
Maximum180
Range175
Interquartile range (IQR)27

Descriptive statistics

Standard deviation27.85541778
Coefficient of variation (CV)0.7881749902
Kurtosis8.059156591
Mean35.34166667
Median Absolute Deviation (MAD)15
Skewness2.482502641
Sum4241
Variance775.9242997
MonotonicityNot monotonic
2022-09-04T23:37:56.083665image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
4525
15.0%
2019
11.4%
3013
 
7.8%
5011
 
6.6%
158
 
4.8%
188
 
4.8%
107
 
4.2%
1206
 
3.6%
253
 
1.8%
422
 
1.2%
Other values (15)18
 
10.8%
(Missing)47
28.1%
ValueCountFrequency (%)
52
 
1.2%
61
 
0.6%
82
 
1.2%
91
 
0.6%
107
4.2%
111
 
0.6%
121
 
0.6%
141
 
0.6%
158
4.8%
188
4.8%
ValueCountFrequency (%)
1801
 
0.6%
1206
 
3.6%
602
 
1.2%
5011
6.6%
481
 
0.6%
4525
15.0%
422
 
1.2%
401
 
0.6%
381
 
0.6%
351
 
0.6%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct36
Distinct (%)23.1%
Missing11
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean35.03205128
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:56.261754image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile9.75
Q118
median30
Q346
95-th percentile60
Maximum180
Range175
Interquartile range (IQR)28

Descriptive statistics

Standard deviation25.7061358
Coefficient of variation (CV)0.7337890548
Kurtosis8.726648805
Mean35.03205128
Median Absolute Deviation (MAD)15
Skewness2.40982913
Sum5465
Variance660.8054177
MonotonicityNot monotonic
2022-09-04T23:37:56.417900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2019
 
11.4%
4516
 
9.6%
5412
 
7.2%
5011
 
6.6%
3010
 
6.0%
469
 
5.4%
189
 
5.4%
238
 
4.8%
105
 
3.0%
255
 
3.0%
Other values (26)52
31.1%
(Missing)11
 
6.6%
ValueCountFrequency (%)
52
 
1.2%
61
 
0.6%
71
 
0.6%
83
1.8%
91
 
0.6%
105
3.0%
114
2.4%
124
2.4%
131
 
0.6%
142
 
1.2%
ValueCountFrequency (%)
1801
 
0.6%
1262
 
1.2%
1203
 
1.8%
981
 
0.6%
603
 
1.8%
5412
7.2%
5011
6.6%
482
 
1.2%
469
5.4%
4516
9.6%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct67
Distinct (%)40.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2020-12-11
32 
2020-08-30
16 
2020-12-04
 
8
2019-06-16
 
8
2019-11-22
 
8
Other values (62)
95 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1670
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)26.9%

Sample

1st row2015-02-13
2nd row2020-05-29
3rd row2020-11-27
4th row2020-11-30
5th row2015-06-26

Common Values

ValueCountFrequency (%)
2020-12-1132
19.2%
2020-08-3016
 
9.6%
2020-12-048
 
4.8%
2019-06-168
 
4.8%
2019-11-228
 
4.8%
2019-12-067
 
4.2%
2020-09-076
 
3.6%
2020-12-105
 
3.0%
2020-11-194
 
2.4%
2020-11-274
 
2.4%
Other values (57)69
41.3%

Length

2022-09-04T23:37:56.572066image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1132
19.2%
2020-08-3016
 
9.6%
2020-12-048
 
4.8%
2019-11-228
 
4.8%
2019-06-168
 
4.8%
2019-12-067
 
4.2%
2020-09-076
 
3.6%
2020-12-105
 
3.0%
2020-11-194
 
2.4%
2020-11-274
 
2.4%
Other values (57)69
41.3%

Most occurring characters

ValueCountFrequency (%)
0416
24.9%
2387
23.2%
-334
20.0%
1314
18.8%
958
 
3.5%
637
 
2.2%
832
 
1.9%
329
 
1.7%
726
 
1.6%
422
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1336
80.0%
Dash Punctuation334
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0416
31.1%
2387
29.0%
1314
23.5%
958
 
4.3%
637
 
2.8%
832
 
2.4%
329
 
2.2%
726
 
1.9%
422
 
1.6%
515
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
-334
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0416
24.9%
2387
23.2%
-334
20.0%
1314
18.8%
958
 
3.5%
637
 
2.2%
832
 
1.9%
329
 
1.7%
726
 
1.6%
422
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0416
24.9%
2387
23.2%
-334
20.0%
1314
18.8%
958
 
3.5%
637
 
2.2%
832
 
1.9%
329
 
1.7%
726
 
1.6%
422
 
1.3%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct23
Distinct (%)25.6%
Missing77
Missing (%)46.1%
Memory size1.4 KiB
2020-12-11
43 
2022-05-06
10 
2021-01-01
2020-12-18
 
4
2020-12-25
 
4
Other values (18)
24 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters900
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)13.3%

Sample

1st row2020-12-18
2nd row2020-12-11
3rd row2020-12-11
4th row2021-01-04
5th row2021-01-04

Common Values

ValueCountFrequency (%)
2020-12-1143
25.7%
2022-05-0610
 
6.0%
2021-01-015
 
3.0%
2020-12-184
 
2.4%
2020-12-254
 
2.4%
2021-01-022
 
1.2%
2021-01-142
 
1.2%
2020-12-172
 
1.2%
2021-01-042
 
1.2%
2021-01-222
 
1.2%
Other values (13)14
 
8.4%
(Missing)77
46.1%

Length

2022-09-04T23:37:56.670983image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1143
47.8%
2022-05-0610
 
11.1%
2021-01-015
 
5.6%
2020-12-184
 
4.4%
2020-12-254
 
4.4%
2021-01-022
 
2.2%
2021-01-142
 
2.2%
2020-12-172
 
2.2%
2021-01-042
 
2.2%
2021-01-222
 
2.2%
Other values (13)14
 
15.6%

Most occurring characters

ValueCountFrequency (%)
2268
29.8%
0205
22.8%
1201
22.3%
-180
20.0%
517
 
1.9%
611
 
1.2%
86
 
0.7%
46
 
0.7%
73
 
0.3%
92
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number720
80.0%
Dash Punctuation180
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2268
37.2%
0205
28.5%
1201
27.9%
517
 
2.4%
611
 
1.5%
86
 
0.8%
46
 
0.8%
73
 
0.4%
92
 
0.3%
31
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
-180
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common900
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2268
29.8%
0205
22.8%
1201
22.3%
-180
20.0%
517
 
1.9%
611
 
1.2%
86
 
0.7%
46
 
0.7%
73
 
0.3%
92
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2268
29.8%
0205
22.8%
1201
22.3%
-180
20.0%
517
 
1.9%
611
 
1.2%
86
 
0.7%
46
 
0.7%
73
 
0.3%
92
 
0.2%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct78
Distinct (%)52.3%
Missing18
Missing (%)10.8%
Memory size1.4 KiB
https://www.zee5.com/zee5originals/details/bebaakee/0-6-2909
16 
https://www.amazon.com/dp/B08NMC79YB/
10 
https://www.hotstar.com/in/tv/triples/1260048875?utm_source=gwa
 
8
https://www.netflix.com/title/81033361
 
8
https://areena.yle.fi/1-50284041
 
8
Other values (73)
99 

Length

Max length250
Median length85
Mean length55.65100671
Min length24

Characters and Unicode

Total characters8292
Distinct characters73
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)38.9%

Sample

1st rowhttp://seasonvar.ru/serial-11488-Po_sezonu_Videodajdzhest_Seasonvar.html
2nd rowhttps://www.ivi.ru/watch/chuma-2020
3rd rowhttps://www.ivi.ru/watch/zakon-i-besporyadok
4th rowhttp://epic-media.ru/project/kotiki
5th rowhttp://www.bilibili.com/bangumi/%E7%8B%90%E5%A6%96%E5%B0%8F%E7%BA%A2%E5%A8%98/

Common Values

ValueCountFrequency (%)
https://www.zee5.com/zee5originals/details/bebaakee/0-6-290916
 
9.6%
https://www.amazon.com/dp/B08NMC79YB/10
 
6.0%
https://www.hotstar.com/in/tv/triples/1260048875?utm_source=gwa8
 
4.8%
https://www.netflix.com/title/810333618
 
4.8%
https://areena.yle.fi/1-502840418
 
4.8%
https://www.amazon.com/gp/video/detail/B086HWFFCS/7
 
4.2%
https://www.hulu.com/series/madagascar-a-little-wild-7a11e023-5762-4980-bfce-7f337e4c28ef6
 
3.6%
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d4
 
2.4%
https://www.cmore.se/serie/208411-lassemajas-detektivbyra2
 
1.2%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
1.2%
Other values (68)78
46.7%
(Missing)18
 
10.8%

Length

2022-09-04T23:37:56.797248image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.zee5.com/zee5originals/details/bebaakee/0-6-290916
 
10.7%
https://www.amazon.com/dp/b08nmc79yb10
 
6.7%
https://www.hotstar.com/in/tv/triples/1260048875?utm_source=gwa8
 
5.4%
https://www.netflix.com/title/810333618
 
5.4%
https://areena.yle.fi/1-502840418
 
5.4%
https://www.amazon.com/gp/video/detail/b086hwffcs7
 
4.7%
https://www.hulu.com/series/madagascar-a-little-wild-7a11e023-5762-4980-bfce-7f337e4c28ef6
 
4.0%
https://v.youku.com/v_show/id_xndk1mzy2nzgwna==.html?spm=a2h0c.8166622.phonesokuprogram_1.dtitle&s=aaed627feea749d7a99d4
 
2.7%
https://www.disneyplus.com/en-gb/series/the-wonderful-world-of-mickey-mouse/6pvlulzeynjs2
 
1.3%
https://www.tytnetwork.com2
 
1.3%
Other values (68)78
52.3%

Most occurring characters

ValueCountFrequency (%)
/680
 
8.2%
t558
 
6.7%
e482
 
5.8%
w397
 
4.8%
s390
 
4.7%
a338
 
4.1%
o334
 
4.0%
.311
 
3.8%
i301
 
3.6%
h259
 
3.1%
Other values (63)4242
51.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5259
63.4%
Other Punctuation1238
 
14.9%
Decimal Number1097
 
13.2%
Uppercase Letter418
 
5.0%
Dash Punctuation197
 
2.4%
Math Symbol43
 
0.5%
Connector Punctuation40
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t558
 
10.6%
e482
 
9.2%
w397
 
7.5%
s390
 
7.4%
a338
 
6.4%
o334
 
6.4%
i301
 
5.7%
h259
 
4.9%
m246
 
4.7%
p230
 
4.4%
Other values (16)1724
32.8%
Uppercase Letter
ValueCountFrequency (%)
B43
 
10.3%
N35
 
8.4%
C29
 
6.9%
A25
 
6.0%
P24
 
5.7%
E23
 
5.5%
F23
 
5.5%
S23
 
5.5%
Y21
 
5.0%
M20
 
4.8%
Other values (16)152
36.4%
Decimal Number
ValueCountFrequency (%)
0176
16.0%
1129
11.8%
2120
10.9%
8111
10.1%
6110
10.0%
998
8.9%
595
8.7%
790
8.2%
488
8.0%
380
7.3%
Other Punctuation
ValueCountFrequency (%)
/680
54.9%
.311
25.1%
:167
 
13.5%
%48
 
3.9%
?23
 
1.9%
&9
 
0.7%
Math Symbol
ValueCountFrequency (%)
=40
93.0%
+2
 
4.7%
~1
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
-197
100.0%
Connector Punctuation
ValueCountFrequency (%)
_40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5677
68.5%
Common2615
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t558
 
9.8%
e482
 
8.5%
w397
 
7.0%
s390
 
6.9%
a338
 
6.0%
o334
 
5.9%
i301
 
5.3%
h259
 
4.6%
m246
 
4.3%
p230
 
4.1%
Other values (42)2142
37.7%
Common
ValueCountFrequency (%)
/680
26.0%
.311
11.9%
-197
 
7.5%
0176
 
6.7%
:167
 
6.4%
1129
 
4.9%
2120
 
4.6%
8111
 
4.2%
6110
 
4.2%
998
 
3.7%
Other values (11)516
19.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII8292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/680
 
8.2%
t558
 
6.7%
e482
 
5.8%
w397
 
4.8%
s390
 
4.7%
a338
 
4.1%
o334
 
4.0%
.311
 
3.8%
i301
 
3.6%
h259
 
3.1%
Other values (63)4242
51.2%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
115 
12:00
20 
00:01
 
8
20:00
 
7
18:00
 
5
Other values (7)
12 

Length

Max length5
Median length0
Mean length1.556886228
Min length0

Characters and Unicode

Total characters260
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)1.8%

Sample

1st row
2nd row
3rd row12:00
4th row10:00
5th row

Common Values

ValueCountFrequency (%)
115
68.9%
12:0020
 
12.0%
00:018
 
4.8%
20:007
 
4.2%
18:005
 
3.0%
21:003
 
1.8%
10:002
 
1.2%
06:002
 
1.2%
00:002
 
1.2%
19:001
 
0.6%
Other values (2)2
 
1.2%

Length

2022-09-04T23:37:56.921184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
12:0020
38.5%
00:018
 
15.4%
20:007
 
13.5%
18:005
 
9.6%
21:003
 
5.8%
10:002
 
3.8%
06:002
 
3.8%
00:002
 
3.8%
19:001
 
1.9%
20:501
 
1.9%

Most occurring characters

ValueCountFrequency (%)
0127
48.8%
:52
20.0%
139
 
15.0%
233
 
12.7%
85
 
1.9%
62
 
0.8%
91
 
0.4%
51
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number208
80.0%
Other Punctuation52
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0127
61.1%
139
 
18.8%
233
 
15.9%
85
 
2.4%
62
 
1.0%
91
 
0.5%
51
 
0.5%
Other Punctuation
ValueCountFrequency (%)
:52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common260
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0127
48.8%
:52
20.0%
139
 
15.0%
233
 
12.7%
85
 
1.9%
62
 
0.8%
91
 
0.4%
51
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII260
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0127
48.8%
:52
20.0%
139
 
15.0%
233
 
12.7%
85
 
1.9%
62
 
0.8%
91
 
0.4%
51
 
0.4%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.4 KiB

_embedded.show.rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct7
Distinct (%)26.9%
Missing141
Missing (%)84.4%
Infinite0
Infinite (%)0.0%
Mean6.638461538
Minimum4.4
Maximum8.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:57.003183image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4.4
5-th percentile5.25
Q16.7
median6.7
Q36.7
95-th percentile7.2
Maximum8.6
Range4.2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7217073773
Coefficient of variation (CV)0.1087160592
Kurtosis5.525939428
Mean6.638461538
Median Absolute Deviation (MAD)0
Skewness-0.8998398768
Sum172.6
Variance0.5208615385
MonotonicityNot monotonic
2022-09-04T23:37:57.114231image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
6.718
 
10.8%
7.23
 
1.8%
61
 
0.6%
6.41
 
0.6%
8.61
 
0.6%
51
 
0.6%
4.41
 
0.6%
(Missing)141
84.4%
ValueCountFrequency (%)
4.41
 
0.6%
51
 
0.6%
61
 
0.6%
6.41
 
0.6%
6.718
10.8%
7.23
 
1.8%
8.61
 
0.6%
ValueCountFrequency (%)
8.61
 
0.6%
7.23
 
1.8%
6.718
10.8%
6.41
 
0.6%
61
 
0.6%
51
 
0.6%
4.41
 
0.6%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct50
Distinct (%)29.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.86826347
Minimum2
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:57.259398image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.3
Q116
median29
Q356.5
95-th percentile94
Maximum100
Range98
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation27.08699748
Coefficient of variation (CV)0.734696862
Kurtosis-0.4829888995
Mean36.86826347
Median Absolute Deviation (MAD)14
Skewness0.7670040353
Sum6157
Variance733.7054325
MonotonicityNot monotonic
2022-09-04T23:37:57.467465image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1618
 
10.8%
4711
 
6.6%
9410
 
6.0%
29
 
5.4%
189
 
5.4%
818
 
4.8%
608
 
4.8%
178
 
4.8%
238
 
4.8%
305
 
3.0%
Other values (40)73
43.7%
ValueCountFrequency (%)
29
5.4%
33
 
1.8%
43
 
1.8%
51
 
0.6%
61
 
0.6%
71
 
0.6%
82
 
1.2%
92
 
1.2%
143
 
1.8%
151
 
0.6%
ValueCountFrequency (%)
1001
 
0.6%
971
 
0.6%
9410
6.0%
818
4.8%
792
 
1.2%
772
 
1.2%
751
 
0.6%
691
 
0.6%
682
 
1.2%
662
 
1.2%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing167
Missing (%)100.0%
Memory size1.4 KiB

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct47
Distinct (%)28.5%
Missing2
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean159.4121212
Minimum1
Maximum516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:57.642940image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q121
median118
Q3287
95-th percentile376
Maximum516
Range515
Interquartile range (IQR)266

Descriptive statistics

Standard deviation144.2672819
Coefficient of variation (CV)0.9049956855
Kurtosis-1.04899989
Mean159.4121212
Median Absolute Deviation (MAD)106
Skewness0.5249215216
Sum26303
Variance20813.04863
MonotonicityNot monotonic
2022-09-04T23:37:58.017200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
2118
 
10.8%
317
 
10.2%
35816
 
9.6%
2208
 
4.8%
3768
 
4.8%
1188
 
4.8%
1648
 
4.8%
18
 
4.8%
1047
 
4.2%
26
 
3.6%
Other values (37)61
36.5%
ValueCountFrequency (%)
18
4.8%
26
 
3.6%
317
10.2%
121
 
0.6%
151
 
0.6%
2118
10.8%
303
 
1.8%
451
 
0.6%
513
 
1.8%
561
 
0.6%
ValueCountFrequency (%)
5161
 
0.6%
5101
 
0.6%
4641
 
0.6%
4401
 
0.6%
4101
 
0.6%
4051
 
0.6%
3768
4.8%
3671
 
0.6%
3651
 
0.6%
35816
9.6%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct47
Distinct (%)28.5%
Missing2
Missing (%)1.2%
Memory size1.4 KiB
YouTube
18 
Prime Video
17 
ZEE5
16 
Yle Areena
 
8
Cosmote TV
 
8
Other values (42)
98 

Length

Max length15
Median length12
Mean length7.993939394
Min length3

Characters and Unicode

Total characters1319
Distinct characters54
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)14.5%

Sample

1st rowSeasonvar
2nd rowivi
3rd rowivi
4th rowEpic Media
5th rowBilibili

Common Values

ValueCountFrequency (%)
YouTube18
 
10.8%
Prime Video17
 
10.2%
ZEE516
 
9.6%
Yle Areena8
 
4.8%
Cosmote TV8
 
4.8%
Youku8
 
4.8%
Disney+ Hotstar8
 
4.8%
Netflix8
 
4.8%
Tencent QQ7
 
4.2%
Hulu6
 
3.6%
Other values (37)61
36.5%

Length

2022-09-04T23:37:58.167099image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube18
 
7.7%
video17
 
7.3%
prime17
 
7.3%
zee516
 
6.8%
tv14
 
6.0%
disney14
 
6.0%
yle8
 
3.4%
areena8
 
3.4%
cosmote8
 
3.4%
youku8
 
3.4%
Other values (53)106
45.3%

Most occurring characters

ValueCountFrequency (%)
e147
 
11.1%
i96
 
7.3%
o86
 
6.5%
69
 
5.2%
u67
 
5.1%
t55
 
4.2%
r52
 
3.9%
T47
 
3.6%
n46
 
3.5%
s45
 
3.4%
Other values (44)609
46.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter846
64.1%
Uppercase Letter366
27.7%
Space Separator69
 
5.2%
Math Symbol21
 
1.6%
Decimal Number17
 
1.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T47
12.8%
V43
11.7%
Y39
10.7%
E36
9.8%
P24
 
6.6%
N22
 
6.0%
Q19
 
5.2%
D18
 
4.9%
Z17
 
4.6%
C16
 
4.4%
Other values (15)85
23.2%
Lowercase Letter
ValueCountFrequency (%)
e147
17.4%
i96
11.3%
o86
10.2%
u67
 
7.9%
t55
 
6.5%
r52
 
6.1%
n46
 
5.4%
s45
 
5.3%
a44
 
5.2%
l35
 
4.1%
Other values (14)173
20.4%
Math Symbol
ValueCountFrequency (%)
+20
95.2%
|1
 
4.8%
Decimal Number
ValueCountFrequency (%)
516
94.1%
21
 
5.9%
Space Separator
ValueCountFrequency (%)
69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1212
91.9%
Common107
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e147
 
12.1%
i96
 
7.9%
o86
 
7.1%
u67
 
5.5%
t55
 
4.5%
r52
 
4.3%
T47
 
3.9%
n46
 
3.8%
s45
 
3.7%
a44
 
3.6%
Other values (39)527
43.5%
Common
ValueCountFrequency (%)
69
64.5%
+20
 
18.7%
516
 
15.0%
21
 
0.9%
|1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII1319
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e147
 
11.1%
i96
 
7.3%
o86
 
6.5%
69
 
5.2%
u67
 
5.1%
t55
 
4.2%
r52
 
3.9%
T47
 
3.6%
n46
 
3.5%
s45
 
3.4%
Other values (44)609
46.2%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct18
Distinct (%)19.4%
Missing74
Missing (%)44.3%
Memory size1.4 KiB
China
19 
India
17 
United States
15 
Finland
Greece
Other values (13)
26 

Length

Max length18
Median length13
Mean length7.946236559
Min length5

Characters and Unicode

Total characters739
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)8.6%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowRussian Federation
4th rowRussian Federation
5th rowChina

Common Values

ValueCountFrequency (%)
China19
 
11.4%
India17
 
10.2%
United States15
 
9.0%
Finland8
 
4.8%
Greece8
 
4.8%
Norway6
 
3.6%
Russian Federation5
 
3.0%
Korea, Republic of3
 
1.8%
Spain2
 
1.2%
Sweden2
 
1.2%
Other values (8)8
 
4.8%
(Missing)74
44.3%

Length

2022-09-04T23:37:58.294107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china19
16.0%
india17
14.3%
united15
12.6%
states15
12.6%
finland8
6.7%
greece8
6.7%
norway6
 
5.0%
russian5
 
4.2%
federation5
 
4.2%
republic3
 
2.5%
Other values (12)18
15.1%

Most occurring characters

ValueCountFrequency (%)
a92
12.4%
n85
11.5%
e78
 
10.6%
i77
 
10.4%
t52
 
7.0%
d49
 
6.6%
s27
 
3.7%
r26
 
3.5%
26
 
3.5%
C20
 
2.7%
Other values (26)207
28.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter594
80.4%
Uppercase Letter116
 
15.7%
Space Separator26
 
3.5%
Other Punctuation3
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a92
15.5%
n85
14.3%
e78
13.1%
i77
13.0%
t52
8.8%
d49
8.2%
s27
 
4.5%
r26
 
4.4%
h20
 
3.4%
o18
 
3.0%
Other values (11)70
11.8%
Uppercase Letter
ValueCountFrequency (%)
C20
17.2%
S19
16.4%
I17
14.7%
U15
12.9%
F13
11.2%
G9
7.8%
R8
 
6.9%
N7
 
6.0%
K3
 
2.6%
B2
 
1.7%
Other values (3)3
 
2.6%
Space Separator
ValueCountFrequency (%)
26
100.0%
Other Punctuation
ValueCountFrequency (%)
,3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin710
96.1%
Common29
 
3.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a92
13.0%
n85
12.0%
e78
11.0%
i77
10.8%
t52
 
7.3%
d49
 
6.9%
s27
 
3.8%
r26
 
3.7%
C20
 
2.8%
h20
 
2.8%
Other values (24)184
25.9%
Common
ValueCountFrequency (%)
26
89.7%
,3
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII739
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a92
12.4%
n85
11.5%
e78
 
10.6%
i77
 
10.4%
t52
 
7.0%
d49
 
6.6%
s27
 
3.7%
r26
 
3.5%
26
 
3.5%
C20
 
2.7%
Other values (26)207
28.0%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct18
Distinct (%)19.4%
Missing74
Missing (%)44.3%
Memory size1.4 KiB
CN
19 
IN
17 
US
15 
FI
GR
Other values (13)
26 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters186
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)8.6%

Sample

1st rowRU
2nd rowRU
3rd rowRU
4th rowRU
5th rowCN

Common Values

ValueCountFrequency (%)
CN19
 
11.4%
IN17
 
10.2%
US15
 
9.0%
FI8
 
4.8%
GR8
 
4.8%
NO6
 
3.6%
RU5
 
3.0%
KR3
 
1.8%
ES2
 
1.2%
SE2
 
1.2%
Other values (8)8
 
4.8%
(Missing)74
44.3%

Length

2022-09-04T23:37:58.456493image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn19
20.4%
in17
18.3%
us15
16.1%
fi8
8.6%
gr8
8.6%
no6
 
6.5%
ru5
 
5.4%
kr3
 
3.2%
se2
 
2.2%
es2
 
2.2%
Other values (8)8
8.6%

Most occurring characters

ValueCountFrequency (%)
N43
23.1%
I25
13.4%
C20
10.8%
U20
10.8%
S19
10.2%
R17
 
9.1%
F8
 
4.3%
G8
 
4.3%
E6
 
3.2%
O6
 
3.2%
Other values (10)14
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter186
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N43
23.1%
I25
13.4%
C20
10.8%
U20
10.8%
S19
10.2%
R17
 
9.1%
F8
 
4.3%
G8
 
4.3%
E6
 
3.2%
O6
 
3.2%
Other values (10)14
 
7.5%

Most occurring scripts

ValueCountFrequency (%)
Latin186
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N43
23.1%
I25
13.4%
C20
10.8%
U20
10.8%
S19
10.2%
R17
 
9.1%
F8
 
4.3%
G8
 
4.3%
E6
 
3.2%
O6
 
3.2%
Other values (10)14
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII186
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N43
23.1%
I25
13.4%
C20
10.8%
U20
10.8%
S19
10.2%
R17
 
9.1%
F8
 
4.3%
G8
 
4.3%
E6
 
3.2%
O6
 
3.2%
Other values (10)14
 
7.5%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct18
Distinct (%)19.4%
Missing74
Missing (%)44.3%
Memory size1.4 KiB
Asia/Shanghai
19 
Asia/Kolkata
17 
America/New_York
15 
Europe/Helsinki
Europe/Athens
Other values (13)
26 

Length

Max length16
Median length15
Mean length13.44086022
Min length10

Characters and Unicode

Total characters1250
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)8.6%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Kamchatka
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai19
 
11.4%
Asia/Kolkata17
 
10.2%
America/New_York15
 
9.0%
Europe/Helsinki8
 
4.8%
Europe/Athens8
 
4.8%
Europe/Oslo6
 
3.6%
Asia/Kamchatka5
 
3.0%
Asia/Seoul3
 
1.8%
Europe/Madrid2
 
1.2%
Europe/Stockholm2
 
1.2%
Other values (8)8
 
4.8%
(Missing)74
44.3%

Length

2022-09-04T23:37:58.555501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai19
20.4%
asia/kolkata17
18.3%
america/new_york15
16.1%
europe/helsinki8
8.6%
europe/athens8
8.6%
europe/oslo6
 
6.5%
asia/kamchatka5
 
5.4%
asia/seoul3
 
3.2%
europe/stockholm2
 
2.2%
europe/madrid2
 
2.2%
Other values (8)8
8.6%

Most occurring characters

ValueCountFrequency (%)
a156
 
12.5%
i104
 
8.3%
/93
 
7.4%
e84
 
6.7%
o80
 
6.4%
s74
 
5.9%
A72
 
5.8%
r67
 
5.4%
h55
 
4.4%
k48
 
3.8%
Other values (26)417
33.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter941
75.3%
Uppercase Letter201
 
16.1%
Other Punctuation93
 
7.4%
Connector Punctuation15
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a156
16.6%
i104
11.1%
e84
8.9%
o80
8.5%
s74
 
7.9%
r67
 
7.1%
h55
 
5.8%
k48
 
5.1%
n40
 
4.3%
l38
 
4.0%
Other values (12)195
20.7%
Uppercase Letter
ValueCountFrequency (%)
A72
35.8%
E30
14.9%
S24
 
11.9%
K23
 
11.4%
N16
 
8.0%
Y15
 
7.5%
H9
 
4.5%
O6
 
3.0%
M2
 
1.0%
B2
 
1.0%
Other values (2)2
 
1.0%
Other Punctuation
ValueCountFrequency (%)
/93
100.0%
Connector Punctuation
ValueCountFrequency (%)
_15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1142
91.4%
Common108
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a156
13.7%
i104
 
9.1%
e84
 
7.4%
o80
 
7.0%
s74
 
6.5%
A72
 
6.3%
r67
 
5.9%
h55
 
4.8%
k48
 
4.2%
n40
 
3.5%
Other values (24)362
31.7%
Common
ValueCountFrequency (%)
/93
86.1%
_15
 
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII1250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a156
 
12.5%
i104
 
8.3%
/93
 
7.4%
e84
 
6.7%
o80
 
6.4%
s74
 
5.9%
A72
 
5.8%
r67
 
5.4%
h55
 
4.4%
k48
 
3.8%
Other values (26)417
33.4%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct19
Distinct (%)22.6%
Missing83
Missing (%)49.7%
Memory size1.4 KiB
https://www.youtube.com
18 
https://www.primevideo.com
17 
https://www.netflix.com/
https://v.qq.com/
https://www.disneyplus.com/
Other values (14)
28 

Length

Max length30
Median length26
Mean length23.0952381
Min length17

Characters and Unicode

Total characters1940
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)9.5%

Sample

1st rowhttps://www.ivi.ru/
2nd rowhttps://www.ivi.ru/
3rd rowhttps://v.qq.com/
4th rowhttps://v.qq.com/
5th rowhttps://v.qq.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com18
 
10.8%
https://www.primevideo.com17
 
10.2%
https://www.netflix.com/8
 
4.8%
https://v.qq.com/7
 
4.2%
https://www.disneyplus.com/6
 
3.6%
https://www.hulu.com/6
 
3.6%
https://www.iq.com/5
 
3.0%
https://tv.naver.com/3
 
1.8%
https://www.discoveryplus.com/2
 
1.2%
https://www.ivi.ru/2
 
1.2%
Other values (9)10
 
6.0%
(Missing)83
49.7%

Length

2022-09-04T23:37:58.692703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com18
21.4%
https://www.primevideo.com17
20.2%
https://www.netflix.com8
9.5%
https://v.qq.com7
 
8.3%
https://www.disneyplus.com6
 
7.1%
https://www.hulu.com6
 
7.1%
https://www.iq.com5
 
6.0%
https://tv.naver.com3
 
3.6%
https://www.viki.com2
 
2.4%
https://www.ivi.ru2
 
2.4%
Other values (9)10
11.9%

Most occurring characters

ValueCountFrequency (%)
w220
11.3%
/215
11.1%
t205
 
10.6%
.167
 
8.6%
o121
 
6.2%
p113
 
5.8%
s103
 
5.3%
m99
 
5.1%
h91
 
4.7%
c84
 
4.3%
Other values (17)522
26.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1474
76.0%
Other Punctuation466
 
24.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w220
14.9%
t205
13.9%
o121
8.2%
p113
 
7.7%
s103
 
7.0%
m99
 
6.7%
h91
 
6.2%
c84
 
5.7%
e77
 
5.2%
i67
 
4.5%
Other values (14)294
19.9%
Other Punctuation
ValueCountFrequency (%)
/215
46.1%
.167
35.8%
:84
 
18.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1474
76.0%
Common466
 
24.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w220
14.9%
t205
13.9%
o121
8.2%
p113
 
7.7%
s103
 
7.0%
m99
 
6.7%
h91
 
6.2%
c84
 
5.7%
e77
 
5.2%
i67
 
4.5%
Other values (14)294
19.9%
Common
ValueCountFrequency (%)
/215
46.1%
.167
35.8%
:84
 
18.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w220
11.3%
/215
11.1%
t205
 
10.6%
.167
 
8.6%
o121
 
6.2%
p113
 
5.8%
s103
 
5.3%
m99
 
5.1%
h91
 
4.7%
c84
 
4.3%
Other values (17)522
26.9%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing167
Missing (%)100.0%
Memory size1.4 KiB

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)66.7%
Missing164
Missing (%)98.2%
Memory size1.4 KiB
34149.0
47170.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters21
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row47170.0
2nd row34149.0
3rd row34149.0

Common Values

ValueCountFrequency (%)
34149.02
 
1.2%
47170.01
 
0.6%
(Missing)164
98.2%

Length

2022-09-04T23:37:58.830673image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:37:58.973488image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
34149.02
66.7%
47170.01
33.3%

Most occurring characters

ValueCountFrequency (%)
45
23.8%
04
19.0%
13
14.3%
.3
14.3%
32
 
9.5%
92
 
9.5%
72
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number18
85.7%
Other Punctuation3
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
45
27.8%
04
22.2%
13
16.7%
32
 
11.1%
92
 
11.1%
72
 
11.1%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
45
23.8%
04
19.0%
13
14.3%
.3
14.3%
32
 
9.5%
92
 
9.5%
72
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45
23.8%
04
19.0%
13
14.3%
.3
14.3%
32
 
9.5%
92
 
9.5%
72
 
9.5%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct63
Distinct (%)47.4%
Missing34
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean369741.6842
Minimum257720
Maximum411923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:37:59.123729image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum257720
5-th percentile302461
Q1363327
median377021
Q3389426
95-th percentile393221.8
Maximum411923
Range154203
Interquartile range (IQR)26099

Descriptive statistics

Standard deviation30072.62955
Coefficient of variation (CV)0.08133416067
Kurtosis3.885299121
Mean369741.6842
Median Absolute Deviation (MAD)12451
Skewness-1.948895037
Sum49175644
Variance904363048
MonotonicityNot monotonic
2022-09-04T23:37:59.304264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38862516
 
9.6%
34982610
 
6.0%
3731878
 
4.8%
3770218
 
4.8%
3932178
 
4.8%
3655568
 
4.8%
3733147
 
4.2%
3911592
 
1.2%
3207252
 
1.2%
3932292
 
1.2%
Other values (53)62
37.1%
(Missing)34
20.4%
ValueCountFrequency (%)
2577202
1.2%
2651931
0.6%
2787932
1.2%
2904171
0.6%
2906861
0.6%
3103112
1.2%
3207252
1.2%
3234201
0.6%
3269621
0.6%
3310952
1.2%
ValueCountFrequency (%)
4119231
 
0.6%
3977341
 
0.6%
3957981
 
0.6%
3939421
 
0.6%
3937431
 
0.6%
3932292
 
1.2%
3932178
4.8%
3931741
 
0.6%
3926821
 
0.6%
3926792
 
1.2%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct43
Distinct (%)39.8%
Missing59
Missing (%)35.3%
Memory size1.4 KiB
tt11992162
16 
tt8633062
10 
tt11321910
tt12299956
tt9731242
Other values (38)
58 

Length

Max length10
Median length10
Mean length9.611111111
Min length9

Characters and Unicode

Total characters1038
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)25.0%

Sample

1st rowtt8871128
2nd rowtt8871128
3rd rowtt11347388
4th rowtt13452364
5th rowtt11492320

Common Values

ValueCountFrequency (%)
tt1199216216
 
9.6%
tt863306210
 
6.0%
tt113219108
 
4.8%
tt122999568
 
4.8%
tt97312428
 
4.8%
tt84478447
 
4.2%
tt117149126
 
3.6%
tt17148102
 
1.2%
tt62647822
 
1.2%
tt135688762
 
1.2%
Other values (33)39
23.4%
(Missing)59
35.3%

Length

2022-09-04T23:37:59.463794image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt1199216216
14.8%
tt863306210
 
9.3%
tt113219108
 
7.4%
tt122999568
 
7.4%
tt97312428
 
7.4%
tt84478447
 
6.5%
tt117149126
 
5.6%
tt88711282
 
1.9%
tt70572622
 
1.9%
tt88650582
 
1.9%
Other values (33)39
36.1%

Most occurring characters

ValueCountFrequency (%)
t216
20.8%
1179
17.2%
2130
12.5%
989
8.6%
673
 
7.0%
872
 
6.9%
469
 
6.6%
368
 
6.6%
057
 
5.5%
756
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number822
79.2%
Lowercase Letter216
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1179
21.8%
2130
15.8%
989
10.8%
673
8.9%
872
8.8%
469
 
8.4%
368
 
8.3%
057
 
6.9%
756
 
6.8%
529
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
t216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common822
79.2%
Latin216
 
20.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1179
21.8%
2130
15.8%
989
10.8%
673
8.9%
872
8.8%
469
 
8.4%
368
 
8.3%
057
 
6.9%
756
 
6.8%
529
 
3.5%
Latin
ValueCountFrequency (%)
t216
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1038
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t216
20.8%
1179
17.2%
2130
12.5%
989
8.6%
673
 
7.0%
872
 
6.9%
469
 
6.6%
368
 
6.6%
057
 
5.5%
756
 
5.4%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct82
Distinct (%)50.6%
Missing5
Missing (%)3.0%
Memory size1.4 KiB
https://static.tvmaze.com/uploads/images/medium_portrait/273/684792.jpg
16 
https://static.tvmaze.com/uploads/images/medium_portrait/408/1021848.jpg
 
10
https://static.tvmaze.com/uploads/images/medium_portrait/237/594908.jpg
 
8
https://static.tvmaze.com/uploads/images/medium_portrait/395/989194.jpg
 
8
https://static.tvmaze.com/uploads/images/medium_portrait/282/706310.jpg
 
8
Other values (77)
112 

Length

Max length72
Median length71
Mean length71.04938272
Min length69

Characters and Unicode

Total characters11510
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)36.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/294/735323.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/285/713441.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/285/713460.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/73/183375.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/273/684792.jpg16
 
9.6%
https://static.tvmaze.com/uploads/images/medium_portrait/408/1021848.jpg10
 
6.0%
https://static.tvmaze.com/uploads/images/medium_portrait/237/594908.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/medium_portrait/395/989194.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/medium_portrait/282/706310.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/medium_portrait/301/753548.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639036.jpg7
 
4.2%
https://static.tvmaze.com/uploads/images/medium_portrait/362/906284.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/289/722651.jpg4
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/288/722130.jpg2
 
1.2%
Other values (72)85
50.9%
(Missing)5
 
3.0%

Length

2022-09-04T23:37:59.655947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/273/684792.jpg16
 
9.9%
https://static.tvmaze.com/uploads/images/medium_portrait/408/1021848.jpg10
 
6.2%
https://static.tvmaze.com/uploads/images/medium_portrait/237/594908.jpg8
 
4.9%
https://static.tvmaze.com/uploads/images/medium_portrait/395/989194.jpg8
 
4.9%
https://static.tvmaze.com/uploads/images/medium_portrait/282/706310.jpg8
 
4.9%
https://static.tvmaze.com/uploads/images/medium_portrait/301/753548.jpg8
 
4.9%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639036.jpg7
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/362/906284.jpg6
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/289/722651.jpg4
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/387/968749.jpg2
 
1.2%
Other values (72)85
52.5%

Most occurring characters

ValueCountFrequency (%)
/1134
 
9.9%
t1134
 
9.9%
a810
 
7.0%
m810
 
7.0%
p648
 
5.6%
s648
 
5.6%
i648
 
5.6%
.486
 
4.2%
e486
 
4.2%
o486
 
4.2%
Other values (22)4220
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8100
70.4%
Other Punctuation1782
 
15.5%
Decimal Number1466
 
12.7%
Connector Punctuation162
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t1134
14.0%
a810
10.0%
m810
10.0%
p648
 
8.0%
s648
 
8.0%
i648
 
8.0%
e486
 
6.0%
o486
 
6.0%
d324
 
4.0%
u324
 
4.0%
Other values (8)1782
22.0%
Decimal Number
ValueCountFrequency (%)
2212
14.5%
8184
12.6%
3152
10.4%
7151
10.3%
9145
9.9%
1141
9.6%
4128
8.7%
0126
8.6%
5118
8.0%
6109
7.4%
Other Punctuation
ValueCountFrequency (%)
/1134
63.6%
.486
27.3%
:162
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8100
70.4%
Common3410
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t1134
14.0%
a810
10.0%
m810
10.0%
p648
 
8.0%
s648
 
8.0%
i648
 
8.0%
e486
 
6.0%
o486
 
6.0%
d324
 
4.0%
u324
 
4.0%
Other values (8)1782
22.0%
Common
ValueCountFrequency (%)
/1134
33.3%
.486
14.3%
2212
 
6.2%
8184
 
5.4%
_162
 
4.8%
:162
 
4.8%
3152
 
4.5%
7151
 
4.4%
9145
 
4.3%
1141
 
4.1%
Other values (4)481
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII11510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/1134
 
9.9%
t1134
 
9.9%
a810
 
7.0%
m810
 
7.0%
p648
 
5.6%
s648
 
5.6%
i648
 
5.6%
.486
 
4.2%
e486
 
4.2%
o486
 
4.2%
Other values (22)4220
36.7%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct82
Distinct (%)50.6%
Missing5
Missing (%)3.0%
Memory size1.4 KiB
https://static.tvmaze.com/uploads/images/original_untouched/273/684792.jpg
16 
https://static.tvmaze.com/uploads/images/original_untouched/408/1021848.jpg
 
10
https://static.tvmaze.com/uploads/images/original_untouched/237/594908.jpg
 
8
https://static.tvmaze.com/uploads/images/original_untouched/395/989194.jpg
 
8
https://static.tvmaze.com/uploads/images/original_untouched/282/706310.jpg
 
8
Other values (77)
112 

Length

Max length75
Median length74
Mean length74.04938272
Min length72

Characters and Unicode

Total characters11996
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)36.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/735323.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/713441.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/713460.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/73/183375.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/273/684792.jpg16
 
9.6%
https://static.tvmaze.com/uploads/images/original_untouched/408/1021848.jpg10
 
6.0%
https://static.tvmaze.com/uploads/images/original_untouched/237/594908.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/original_untouched/395/989194.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/original_untouched/282/706310.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/original_untouched/301/753548.jpg8
 
4.8%
https://static.tvmaze.com/uploads/images/original_untouched/255/639036.jpg7
 
4.2%
https://static.tvmaze.com/uploads/images/original_untouched/362/906284.jpg6
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/289/722651.jpg4
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/288/722130.jpg2
 
1.2%
Other values (72)85
50.9%
(Missing)5
 
3.0%

Length

2022-09-04T23:37:59.830020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/273/684792.jpg16
 
9.9%
https://static.tvmaze.com/uploads/images/original_untouched/408/1021848.jpg10
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/237/594908.jpg8
 
4.9%
https://static.tvmaze.com/uploads/images/original_untouched/395/989194.jpg8
 
4.9%
https://static.tvmaze.com/uploads/images/original_untouched/282/706310.jpg8
 
4.9%
https://static.tvmaze.com/uploads/images/original_untouched/301/753548.jpg8
 
4.9%
https://static.tvmaze.com/uploads/images/original_untouched/255/639036.jpg7
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/362/906284.jpg6
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/289/722651.jpg4
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/387/968749.jpg2
 
1.2%
Other values (72)85
52.5%

Most occurring characters

ValueCountFrequency (%)
/1134
 
9.5%
t972
 
8.1%
a810
 
6.8%
s648
 
5.4%
i648
 
5.4%
o648
 
5.4%
p486
 
4.1%
c486
 
4.1%
.486
 
4.1%
g486
 
4.1%
Other values (23)5192
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8586
71.6%
Other Punctuation1782
 
14.9%
Decimal Number1466
 
12.2%
Connector Punctuation162
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t972
 
11.3%
a810
 
9.4%
s648
 
7.5%
i648
 
7.5%
o648
 
7.5%
p486
 
5.7%
c486
 
5.7%
g486
 
5.7%
m486
 
5.7%
e486
 
5.7%
Other values (9)2430
28.3%
Decimal Number
ValueCountFrequency (%)
2212
14.5%
8184
12.6%
3152
10.4%
7151
10.3%
9145
9.9%
1141
9.6%
4128
8.7%
0126
8.6%
5118
8.0%
6109
7.4%
Other Punctuation
ValueCountFrequency (%)
/1134
63.6%
.486
27.3%
:162
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8586
71.6%
Common3410
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t972
 
11.3%
a810
 
9.4%
s648
 
7.5%
i648
 
7.5%
o648
 
7.5%
p486
 
5.7%
c486
 
5.7%
g486
 
5.7%
m486
 
5.7%
e486
 
5.7%
Other values (9)2430
28.3%
Common
ValueCountFrequency (%)
/1134
33.3%
.486
14.3%
2212
 
6.2%
8184
 
5.4%
:162
 
4.8%
_162
 
4.8%
3152
 
4.5%
7151
 
4.4%
9145
 
4.3%
1141
 
4.1%
Other values (4)481
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII11996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/1134
 
9.5%
t972
 
8.1%
a810
 
6.8%
s648
 
5.4%
i648
 
5.4%
o648
 
5.4%
p486
 
4.1%
c486
 
4.1%
.486
 
4.1%
g486
 
4.1%
Other values (23)5192
43.3%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct77
Distinct (%)51.3%
Missing17
Missing (%)10.2%
Memory size1.4 KiB
<p>Sufiyaan and Imtiaz are like brothers, and together they run one of the biggest media houses in Manali. But what will happen when they both fall for the same woman- Kainaat? And whom will she choose - a good friend or a bebaak lover?</p>
16 
<p>A group of teen girls from different backgrounds must fight for survival after a plane crash strands them on a deserted island. The castaways both clash and bond as they learn more about each other, the secrets they keep, and the traumas they've all endured. There's just one twist to this thrilling Drama - Coming of Age … these girls did not end up on this island by accident.</p>
 
10
<p>A series of murders alarm the police authorities, as strange symbolisms are traced to every crime scene. The eccentric professor of criminology Dimitris Lainis is asked to shed some light on the mystery. </p>
 
8
<p>A teacher starts her job at a high school but is haunted by a suspicious death that occurred there weeks before... and begins fearing for her own life.</p>
 
8
<p>Three besties, one dream café. It's anything but a cakewalk with shifty employees, angry politicians, crazy loan sharks and exes with whys.</p>
 
8
Other values (72)
100 

Length

Max length1360
Median length674.5
Mean length348.2333333
Min length54

Characters and Unicode

Total characters52235
Distinct characters91
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)36.7%

Sample

1st row<p>Weekly videodaydzhest on site seasonvar.ru and creative team viruseproject.tv. In ten minutes, we talk about the most important events of the past week: look down on the set is not yet published projects, sharing the secrets of private life actors consider the prospects for the development of genres and discuss news TV industry! In videodaydzheste you will find only reliable information from Russian and foreign publications, as well as take part in choosing the best show of the month! Our weekly news videodaydzhest will suit every viewer, so gather good company with family and friends, as well as stock up on popcorn - these ten minutes you shock, delight and inform the latest news about your favorite TV projects!</p>
2nd row<p><b>Plague</b> – a Comedy project about how hard it is to survive in the middle ages during the plague. This is a story about the residents of the fictional town of Hamburg, locked in a castle under quarantine. Also locked up in the castle is the Messenger William, who, in fact, brought the news of the plague.</p>
3rd row<p>Lytk-Angeles, the state of Moskvachussets, has always been a quiet town where every gang had its rightful place. The Colombians smoked plantain, the Irish sipped beer, and the Chinese ate noodles. But one day the evil Russian Communists came and brought sugar with them. They slaughtered all the street vendors of plantain, seized control of the production of matryoshka dolls (a traditional Yugoslav business) and got the whole city hooked on white powder.</p><p>This will be the last case for Eustace Lynch. Famous for his lucky tattoo, an Irish gangster comes to Lytk-Angeles from Dublin (also known as Dubna) to get rid of the Communists. At the same time, Sally Raptor, a police officer from palm beach (also known as Gelendzhik) arrives in the city with a similar task.</p><p>Zakon i Besporyadok is a parody of the films of the 80s and 90s that we watched on videotapes with one-voice voice-over as a child, and a tribute to that forever-gone era when the screen belonged entirely to evil Russians, Asian martial artists and drinking detectives in ridiculous hats. Each episode parodies one of your favorite genres: the characters don't change, but they end up in an Asian fighting game, a crime Thriller, or even a neo-noir story.</p>
4th row<p>Buy UCO from childhood grew up in the clan, Ichigo, but their "care" was for him a living Hell. Constant bullying, stealing the Goodies, without which Ycu can not live, and even eternal persecution, from the fair sex turned him into a goner cheapskate who wants to take revenge on his tormentors. But revenge is sweet and the path to it is thorny and to accomplish, UCU need to marry a girl Yes, as soon as possible. But when the heroes just happen? Never! And meeting with the small and the big-eared Fox Susan su su did not just destroy his plans, but starts spinning the wheel of fate that was waiting in the wings for hundreds of years!</p>
5th row<p>Buy UCO from childhood grew up in the clan, Ichigo, but their "care" was for him a living Hell. Constant bullying, stealing the Goodies, without which Ycu can not live, and even eternal persecution, from the fair sex turned him into a goner cheapskate who wants to take revenge on his tormentors. But revenge is sweet and the path to it is thorny and to accomplish, UCU need to marry a girl Yes, as soon as possible. But when the heroes just happen? Never! And meeting with the small and the big-eared Fox Susan su su did not just destroy his plans, but starts spinning the wheel of fate that was waiting in the wings for hundreds of years!</p>

Common Values

ValueCountFrequency (%)
<p>Sufiyaan and Imtiaz are like brothers, and together they run one of the biggest media houses in Manali. But what will happen when they both fall for the same woman- Kainaat? And whom will she choose - a good friend or a bebaak lover?</p>16
 
9.6%
<p>A group of teen girls from different backgrounds must fight for survival after a plane crash strands them on a deserted island. The castaways both clash and bond as they learn more about each other, the secrets they keep, and the traumas they've all endured. There's just one twist to this thrilling Drama - Coming of Age … these girls did not end up on this island by accident.</p>10
 
6.0%
<p>A series of murders alarm the police authorities, as strange symbolisms are traced to every crime scene. The eccentric professor of criminology Dimitris Lainis is asked to shed some light on the mystery. </p>8
 
4.8%
<p>A teacher starts her job at a high school but is haunted by a suspicious death that occurred there weeks before... and begins fearing for her own life.</p>8
 
4.8%
<p>Three besties, one dream café. It's anything but a cakewalk with shifty employees, angry politicians, crazy loan sharks and exes with whys.</p>8
 
4.8%
<p>Join Emily Elizabeth and her big red dog, Clifford, as they explore their island home and go on big new adventures! With a fun and furry new cast of characters and brand-new original songs, Clifford's world, and heart, just keep on growing!</p>7
 
4.2%
<p>Loveable foursome Alex the Lion, Marty the Zebra, Melman the Giraffe and Gloria the Hippo steal the show in <b>Madagascar: A Little Wild</b>. Capturing the iconic personalities of each of the four dynamos, <i>Madagascar: A Little Wild</i> showcases the team as kids residing in their rescue habitat at the Central Park Zoo. They might be small, but like everybody who lands in New York City, these little guys have big dreams and <i>Madagascar: A Little Wild</i> will follow all of their adventures.</p>6
 
3.6%
<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>4
 
2.4%
<p>Proving once again that "the drive-in will never die," iconic horror host and exploitation movie aficionado Joe Bob Briggs is back with an all-new Shudder Original series, hosting weekly Friday night double features streaming live exclusively on Shudder. Every week, The Last Drive-In series offers an eclectic pairing of films, with selections ranging across five decades and running the gamut from horror classics to obscurities and foreign cult favorites. And from time to time, special surprise guests will drop in on Joe Bob and Darcy the Mail Girl.</p>2
 
1.2%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
1.2%
Other values (67)79
47.3%
(Missing)17
 
10.2%

Length

2022-09-04T23:37:59.976555image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the499
 
5.6%
and351
 
4.0%
a295
 
3.3%
of245
 
2.8%
to165
 
1.9%
in151
 
1.7%
they106
 
1.2%
on82
 
0.9%
is79
 
0.9%
as75
 
0.8%
Other values (1919)6786
76.8%

Most occurring characters

ValueCountFrequency (%)
8660
16.6%
e4749
 
9.1%
a3330
 
6.4%
t3215
 
6.2%
o2977
 
5.7%
i2864
 
5.5%
n2844
 
5.4%
s2636
 
5.0%
r2415
 
4.6%
h2174
 
4.2%
Other values (81)16371
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter39476
75.6%
Space Separator8689
 
16.6%
Uppercase Letter1437
 
2.8%
Other Punctuation1418
 
2.7%
Math Symbol945
 
1.8%
Dash Punctuation135
 
0.3%
Decimal Number87
 
0.2%
Format24
 
< 0.1%
Close Punctuation11
 
< 0.1%
Open Punctuation11
 
< 0.1%
Other values (2)2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e4749
12.0%
a3330
 
8.4%
t3215
 
8.1%
o2977
 
7.5%
i2864
 
7.3%
n2844
 
7.2%
s2636
 
6.7%
r2415
 
6.1%
h2174
 
5.5%
l1703
 
4.3%
Other values (20)10569
26.8%
Uppercase Letter
ValueCountFrequency (%)
A155
 
10.8%
T132
 
9.2%
S118
 
8.2%
M110
 
7.7%
C94
 
6.5%
L91
 
6.3%
I76
 
5.3%
W75
 
5.2%
B62
 
4.3%
D51
 
3.5%
Other values (17)473
32.9%
Other Punctuation
ValueCountFrequency (%)
,485
34.2%
.418
29.5%
/245
17.3%
'108
 
7.6%
"42
 
3.0%
?40
 
2.8%
!34
 
2.4%
:29
 
2.0%
10
 
0.7%
;6
 
0.4%
Decimal Number
ValueCountFrequency (%)
024
27.6%
120
23.0%
217
19.5%
87
 
8.0%
95
 
5.7%
74
 
4.6%
34
 
4.6%
54
 
4.6%
41
 
1.1%
61
 
1.1%
Math Symbol
ValueCountFrequency (%)
>472
49.9%
<472
49.9%
+1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
-122
90.4%
7
 
5.2%
6
 
4.4%
Space Separator
ValueCountFrequency (%)
8660
99.7%
 29
 
0.3%
Format
ValueCountFrequency (%)
24
100.0%
Close Punctuation
ValueCountFrequency (%)
)11
100.0%
Open Punctuation
ValueCountFrequency (%)
(11
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin40913
78.3%
Common11322
 
21.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e4749
 
11.6%
a3330
 
8.1%
t3215
 
7.9%
o2977
 
7.3%
i2864
 
7.0%
n2844
 
7.0%
s2636
 
6.4%
r2415
 
5.9%
h2174
 
5.3%
l1703
 
4.2%
Other values (47)12006
29.3%
Common
ValueCountFrequency (%)
8660
76.5%
,485
 
4.3%
>472
 
4.2%
<472
 
4.2%
.418
 
3.7%
/245
 
2.2%
-122
 
1.1%
'108
 
1.0%
"42
 
0.4%
?40
 
0.4%
Other values (24)258
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII52142
99.8%
Punctuation48
 
0.1%
None45
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8660
16.6%
e4749
 
9.1%
a3330
 
6.4%
t3215
 
6.2%
o2977
 
5.7%
i2864
 
5.5%
n2844
 
5.5%
s2636
 
5.1%
r2415
 
4.6%
h2174
 
4.2%
Other values (70)16278
31.2%
None
ValueCountFrequency (%)
 29
64.4%
é8
 
17.8%
Í3
 
6.7%
ø2
 
4.4%
ä2
 
4.4%
á1
 
2.2%
Punctuation
ValueCountFrequency (%)
24
50.0%
10
20.8%
7
 
14.6%
6
 
12.5%
1
 
2.1%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct87
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1636874312
Minimum1604587145
Maximum1662306210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-09-04T23:38:00.126171image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1604587145
5-th percentile1609208875
Q11617309477
median1645107318
Q31656443968
95-th percentile1660909177
Maximum1662306210
Range57719065
Interquartile range (IQR)39134490.5

Descriptive statistics

Standard deviation19522607.96
Coefficient of variation (CV)0.01192676055
Kurtosis-1.633001268
Mean1636874312
Median Absolute Deviation (MAD)14815974
Skewness-0.1908079081
Sum2.7335801 × 1011
Variance3.811322217 × 1014
MonotonicityNot monotonic
2022-09-04T23:38:00.291386image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
161294932016
 
9.6%
165992329210
 
6.0%
16568998808
 
4.8%
16219213638
 
4.8%
16092088758
 
4.8%
16480547578
 
4.8%
16173094777
 
4.2%
16574757236
 
3.6%
16545931514
 
2.4%
16250336672
 
1.2%
Other values (77)90
53.9%
ValueCountFrequency (%)
16045871451
 
0.6%
16078155701
 
0.6%
16078871751
 
0.6%
16084019621
 
0.6%
16092088758
4.8%
16094684031
 
0.6%
16095364481
 
0.6%
16096716402
 
1.2%
16103080041
 
0.6%
16113526801
 
0.6%
ValueCountFrequency (%)
16623062101
0.6%
16622908591
0.6%
16622799521
0.6%
16620118651
0.6%
16619549411
0.6%
16615205871
0.6%
16613636441
0.6%
16611987911
0.6%
16610060421
0.6%
16606831582
1.2%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct87
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
https://api.tvmaze.com/shows/50467
16 
https://api.tvmaze.com/shows/37390
 
10
https://api.tvmaze.com/shows/54381
 
8
https://api.tvmaze.com/shows/51653
 
8
https://api.tvmaze.com/shows/45987
 
8
Other values (82)
117 

Length

Max length34
Median length34
Mean length33.98802395
Min length33

Characters and Unicode

Total characters5676
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)38.3%

Sample

1st rowhttps://api.tvmaze.com/shows/7847
2nd rowhttps://api.tvmaze.com/shows/48402
3rd rowhttps://api.tvmaze.com/shows/52118
4th rowhttps://api.tvmaze.com/shows/52198
5th rowhttps://api.tvmaze.com/shows/20734

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/5046716
 
9.6%
https://api.tvmaze.com/shows/3739010
 
6.0%
https://api.tvmaze.com/shows/543818
 
4.8%
https://api.tvmaze.com/shows/516538
 
4.8%
https://api.tvmaze.com/shows/459878
 
4.8%
https://api.tvmaze.com/shows/604278
 
4.8%
https://api.tvmaze.com/shows/478817
 
4.2%
https://api.tvmaze.com/shows/497216
 
3.6%
https://api.tvmaze.com/shows/524514
 
2.4%
https://api.tvmaze.com/shows/234012
 
1.2%
Other values (77)90
53.9%

Length

2022-09-04T23:38:00.464350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/5046716
 
9.6%
https://api.tvmaze.com/shows/3739010
 
6.0%
https://api.tvmaze.com/shows/543818
 
4.8%
https://api.tvmaze.com/shows/516538
 
4.8%
https://api.tvmaze.com/shows/459878
 
4.8%
https://api.tvmaze.com/shows/604278
 
4.8%
https://api.tvmaze.com/shows/478817
 
4.2%
https://api.tvmaze.com/shows/497216
 
3.6%
https://api.tvmaze.com/shows/524514
 
2.4%
https://api.tvmaze.com/shows/525712
 
1.2%
Other values (77)90
53.9%

Most occurring characters

ValueCountFrequency (%)
/668
 
11.8%
s501
 
8.8%
t501
 
8.8%
h334
 
5.9%
p334
 
5.9%
a334
 
5.9%
o334
 
5.9%
.334
 
5.9%
m334
 
5.9%
e167
 
2.9%
Other values (16)1835
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3674
64.7%
Other Punctuation1169
 
20.6%
Decimal Number833
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s501
13.6%
t501
13.6%
h334
9.1%
p334
9.1%
a334
9.1%
o334
9.1%
m334
9.1%
e167
 
4.5%
w167
 
4.5%
c167
 
4.5%
Other values (3)501
13.6%
Decimal Number
ValueCountFrequency (%)
5145
17.4%
4108
13.0%
193
11.2%
080
9.6%
779
9.5%
275
9.0%
371
8.5%
667
8.0%
859
7.1%
956
 
6.7%
Other Punctuation
ValueCountFrequency (%)
/668
57.1%
.334
28.6%
:167
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin3674
64.7%
Common2002
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/668
33.4%
.334
16.7%
:167
 
8.3%
5145
 
7.2%
4108
 
5.4%
193
 
4.6%
080
 
4.0%
779
 
3.9%
275
 
3.7%
371
 
3.5%
Other values (3)182
 
9.1%
Latin
ValueCountFrequency (%)
s501
13.6%
t501
13.6%
h334
9.1%
p334
9.1%
a334
9.1%
o334
9.1%
m334
9.1%
e167
 
4.5%
w167
 
4.5%
c167
 
4.5%
Other values (3)501
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII5676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/668
 
11.8%
s501
 
8.8%
t501
 
8.8%
h334
 
5.9%
p334
 
5.9%
a334
 
5.9%
o334
 
5.9%
.334
 
5.9%
m334
 
5.9%
e167
 
2.9%
Other values (16)1835
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct87
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
https://api.tvmaze.com/episodes/1995389
16 
https://api.tvmaze.com/episodes/2284348
 
10
https://api.tvmaze.com/episodes/2055651
 
8
https://api.tvmaze.com/episodes/1984085
 
8
https://api.tvmaze.com/episodes/1995067
 
8
Other values (82)
117 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters6513
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)38.3%

Sample

1st rowhttps://api.tvmaze.com/episodes/2338362
2nd rowhttps://api.tvmaze.com/episodes/1961005
3rd rowhttps://api.tvmaze.com/episodes/1976572
4th rowhttps://api.tvmaze.com/episodes/1986873
5th rowhttps://api.tvmaze.com/episodes/2153563

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/199538916
 
9.6%
https://api.tvmaze.com/episodes/228434810
 
6.0%
https://api.tvmaze.com/episodes/20556518
 
4.8%
https://api.tvmaze.com/episodes/19840858
 
4.8%
https://api.tvmaze.com/episodes/19950678
 
4.8%
https://api.tvmaze.com/episodes/23004468
 
4.8%
https://api.tvmaze.com/episodes/20571637
 
4.2%
https://api.tvmaze.com/episodes/23525916
 
3.6%
https://api.tvmaze.com/episodes/19861744
 
2.4%
https://api.tvmaze.com/episodes/20920412
 
1.2%
Other values (77)90
53.9%

Length

2022-09-04T23:38:00.614821image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/199538916
 
9.6%
https://api.tvmaze.com/episodes/228434810
 
6.0%
https://api.tvmaze.com/episodes/20556518
 
4.8%
https://api.tvmaze.com/episodes/19840858
 
4.8%
https://api.tvmaze.com/episodes/19950678
 
4.8%
https://api.tvmaze.com/episodes/23004468
 
4.8%
https://api.tvmaze.com/episodes/20571637
 
4.2%
https://api.tvmaze.com/episodes/23525916
 
3.6%
https://api.tvmaze.com/episodes/19861744
 
2.4%
https://api.tvmaze.com/episodes/19902312
 
1.2%
Other values (77)90
53.9%

Most occurring characters

ValueCountFrequency (%)
/668
 
10.3%
t501
 
7.7%
p501
 
7.7%
s501
 
7.7%
e501
 
7.7%
a334
 
5.1%
i334
 
5.1%
.334
 
5.1%
m334
 
5.1%
o334
 
5.1%
Other values (16)2171
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4175
64.1%
Other Punctuation1169
 
17.9%
Decimal Number1169
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t501
12.0%
p501
12.0%
s501
12.0%
e501
12.0%
a334
8.0%
i334
8.0%
m334
8.0%
o334
8.0%
h167
 
4.0%
d167
 
4.0%
Other values (3)501
12.0%
Decimal Number
ValueCountFrequency (%)
2168
14.4%
9163
13.9%
1135
11.5%
5132
11.3%
8111
9.5%
3106
9.1%
099
8.5%
495
8.1%
784
7.2%
676
6.5%
Other Punctuation
ValueCountFrequency (%)
/668
57.1%
.334
28.6%
:167
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin4175
64.1%
Common2338
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/668
28.6%
.334
14.3%
2168
 
7.2%
:167
 
7.1%
9163
 
7.0%
1135
 
5.8%
5132
 
5.6%
8111
 
4.7%
3106
 
4.5%
099
 
4.2%
Other values (3)255
 
10.9%
Latin
ValueCountFrequency (%)
t501
12.0%
p501
12.0%
s501
12.0%
e501
12.0%
a334
8.0%
i334
8.0%
m334
8.0%
o334
8.0%
h167
 
4.0%
d167
 
4.0%
Other values (3)501
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/668
 
10.3%
t501
 
7.7%
p501
 
7.7%
s501
 
7.7%
e501
 
7.7%
a334
 
5.1%
i334
 
5.1%
.334
 
5.1%
m334
 
5.1%
o334
 
5.1%
Other values (16)2171
33.3%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing162
Missing (%)97.0%
Memory size1.4 KiB
https://api.tvmaze.com/episodes/2338363
https://api.tvmaze.com/episodes/2376728
https://api.tvmaze.com/episodes/2280414
https://api.tvmaze.com/episodes/2332527
https://api.tvmaze.com/episodes/2354255

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters195
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2338363
2nd rowhttps://api.tvmaze.com/episodes/2376728
3rd rowhttps://api.tvmaze.com/episodes/2280414
4th rowhttps://api.tvmaze.com/episodes/2332527
5th rowhttps://api.tvmaze.com/episodes/2354255

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23383631
 
0.6%
https://api.tvmaze.com/episodes/23767281
 
0.6%
https://api.tvmaze.com/episodes/22804141
 
0.6%
https://api.tvmaze.com/episodes/23325271
 
0.6%
https://api.tvmaze.com/episodes/23542551
 
0.6%
(Missing)162
97.0%

Length

2022-09-04T23:38:00.763632image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:38:00.863050image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23383631
20.0%
https://api.tvmaze.com/episodes/23767281
20.0%
https://api.tvmaze.com/episodes/22804141
20.0%
https://api.tvmaze.com/episodes/23325271
20.0%
https://api.tvmaze.com/episodes/23542551
20.0%

Most occurring characters

ValueCountFrequency (%)
/20
 
10.3%
e15
 
7.7%
p15
 
7.7%
s15
 
7.7%
t15
 
7.7%
o10
 
5.1%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
210
 
5.1%
Other values (15)65
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125
64.1%
Other Punctuation35
 
17.9%
Decimal Number35
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e15
12.0%
p15
12.0%
s15
12.0%
t15
12.0%
o10
8.0%
a10
8.0%
i10
8.0%
m10
8.0%
d5
 
4.0%
h5
 
4.0%
Other values (3)15
12.0%
Decimal Number
ValueCountFrequency (%)
210
28.6%
38
22.9%
54
 
11.4%
83
 
8.6%
73
 
8.6%
43
 
8.6%
62
 
5.7%
01
 
2.9%
11
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/20
57.1%
.10
28.6%
:5
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin125
64.1%
Common70
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e15
12.0%
p15
12.0%
s15
12.0%
t15
12.0%
o10
8.0%
a10
8.0%
i10
8.0%
m10
8.0%
d5
 
4.0%
h5
 
4.0%
Other values (3)15
12.0%
Common
ValueCountFrequency (%)
/20
28.6%
.10
14.3%
210
14.3%
38
 
11.4%
:5
 
7.1%
54
 
5.7%
83
 
4.3%
73
 
4.3%
43
 
4.3%
62
 
2.9%
Other values (2)2
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20
 
10.3%
e15
 
7.7%
p15
 
7.7%
s15
 
7.7%
t15
 
7.7%
o10
 
5.1%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
210
 
5.1%
Other values (15)65
33.3%

image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct71
Distinct (%)100.0%
Missing96
Missing (%)57.5%
Memory size1.4 KiB
https://static.tvmaze.com/uploads/images/medium_landscape/294/736863.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/720840.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/720839.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/720838.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/720837.jpg
 
1
Other values (66)
66 

Length

Max length73
Median length72
Mean length72.01408451
Min length72

Characters and Unicode

Total characters5113
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/294/736863.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/285/714186.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726345.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/722471.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/289/722703.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/294/736863.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720840.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720839.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720838.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720837.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720836.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720835.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720834.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/291/727765.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721194.jpg1
 
0.6%
Other values (61)61
36.5%
(Missing)96
57.5%

Length

2022-09-04T23:38:01.016431image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/294/736863.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/290/727239.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/285/714186.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726345.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722471.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/289/722703.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/289/723158.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/289/723213.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/289/723398.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/medium_landscape/291/727599.jpg1
 
1.4%
Other values (61)61
85.9%

Most occurring characters

ValueCountFrequency (%)
/497
 
9.7%
a426
 
8.3%
s355
 
6.9%
t355
 
6.9%
m355
 
6.9%
e284
 
5.6%
p284
 
5.6%
d213
 
4.2%
i213
 
4.2%
c213
 
4.2%
Other values (22)1918
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3621
70.8%
Other Punctuation781
 
15.3%
Decimal Number640
 
12.5%
Connector Punctuation71
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a426
11.8%
s355
9.8%
t355
9.8%
m355
9.8%
e284
 
7.8%
p284
 
7.8%
d213
 
5.9%
i213
 
5.9%
c213
 
5.9%
o142
 
3.9%
Other values (8)781
21.6%
Decimal Number
ValueCountFrequency (%)
2160
25.0%
8143
22.3%
790
14.1%
055
 
8.6%
144
 
6.9%
939
 
6.1%
335
 
5.5%
531
 
4.8%
625
 
3.9%
418
 
2.8%
Other Punctuation
ValueCountFrequency (%)
/497
63.6%
.213
27.3%
:71
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3621
70.8%
Common1492
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a426
11.8%
s355
9.8%
t355
9.8%
m355
9.8%
e284
 
7.8%
p284
 
7.8%
d213
 
5.9%
i213
 
5.9%
c213
 
5.9%
o142
 
3.9%
Other values (8)781
21.6%
Common
ValueCountFrequency (%)
/497
33.3%
.213
14.3%
2160
 
10.7%
8143
 
9.6%
790
 
6.0%
_71
 
4.8%
:71
 
4.8%
055
 
3.7%
144
 
2.9%
939
 
2.6%
Other values (4)109
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII5113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/497
 
9.7%
a426
 
8.3%
s355
 
6.9%
t355
 
6.9%
m355
 
6.9%
e284
 
5.6%
p284
 
5.6%
d213
 
4.2%
i213
 
4.2%
c213
 
4.2%
Other values (22)1918
37.5%

image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct71
Distinct (%)100.0%
Missing96
Missing (%)57.5%
Memory size1.4 KiB
https://static.tvmaze.com/uploads/images/original_untouched/294/736863.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/720840.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/720839.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/720838.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/720837.jpg
 
1
Other values (66)
66 

Length

Max length75
Median length74
Mean length74.01408451
Min length74

Characters and Unicode

Total characters5255
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/736863.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/714186.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726345.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/722471.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/289/722703.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/294/736863.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/720840.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/720839.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/720838.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/720837.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/720836.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/720835.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/720834.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/291/727765.jpg1
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/288/721194.jpg1
 
0.6%
Other values (61)61
36.5%
(Missing)96
57.5%

Length

2022-09-04T23:38:01.108444image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/294/736863.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/290/727239.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/714186.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/290/726345.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/288/722471.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/722703.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/723158.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/723213.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/723398.jpg1
 
1.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/727599.jpg1
 
1.4%
Other values (61)61
85.9%

Most occurring characters

ValueCountFrequency (%)
/497
 
9.5%
t426
 
8.1%
a355
 
6.8%
s284
 
5.4%
o284
 
5.4%
i284
 
5.4%
m213
 
4.1%
u213
 
4.1%
e213
 
4.1%
c213
 
4.1%
Other values (23)2273
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3763
71.6%
Other Punctuation781
 
14.9%
Decimal Number640
 
12.2%
Connector Punctuation71
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t426
 
11.3%
a355
 
9.4%
s284
 
7.5%
o284
 
7.5%
i284
 
7.5%
m213
 
5.7%
u213
 
5.7%
e213
 
5.7%
c213
 
5.7%
g213
 
5.7%
Other values (9)1065
28.3%
Decimal Number
ValueCountFrequency (%)
2160
25.0%
8143
22.3%
790
14.1%
055
 
8.6%
144
 
6.9%
939
 
6.1%
335
 
5.5%
531
 
4.8%
625
 
3.9%
418
 
2.8%
Other Punctuation
ValueCountFrequency (%)
/497
63.6%
.213
27.3%
:71
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3763
71.6%
Common1492
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t426
 
11.3%
a355
 
9.4%
s284
 
7.5%
o284
 
7.5%
i284
 
7.5%
m213
 
5.7%
u213
 
5.7%
e213
 
5.7%
c213
 
5.7%
g213
 
5.7%
Other values (9)1065
28.3%
Common
ValueCountFrequency (%)
/497
33.3%
.213
14.3%
2160
 
10.7%
8143
 
9.6%
790
 
6.0%
_71
 
4.8%
:71
 
4.8%
055
 
3.7%
144
 
2.9%
939
 
2.6%
Other values (4)109
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII5255
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/497
 
9.5%
t426
 
8.1%
a355
 
6.8%
s284
 
5.4%
o284
 
5.4%
i284
 
5.4%
m213
 
4.1%
u213
 
4.1%
e213
 
4.1%
c213
 
4.1%
Other values (23)2273
43.3%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing167
Missing (%)100.0%
Memory size1.4 KiB

_embedded.show.network.id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)80.0%
Missing162
Missing (%)97.0%
Memory size1.4 KiB
339.0
276.0
374.0
78.0

Length

Max length5
Median length5
Mean length4.8
Min length4

Characters and Unicode

Total characters24
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row339.0
2nd row339.0
3rd row276.0
4th row374.0
5th row78.0

Common Values

ValueCountFrequency (%)
339.02
 
1.2%
276.01
 
0.6%
374.01
 
0.6%
78.01
 
0.6%
(Missing)162
97.0%

Length

2022-09-04T23:38:01.253585image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:38:01.520575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
339.02
40.0%
276.01
20.0%
374.01
20.0%
78.01
20.0%

Most occurring characters

ValueCountFrequency (%)
35
20.8%
.5
20.8%
05
20.8%
73
12.5%
92
 
8.3%
21
 
4.2%
61
 
4.2%
41
 
4.2%
81
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number19
79.2%
Other Punctuation5
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
35
26.3%
05
26.3%
73
15.8%
92
 
10.5%
21
 
5.3%
61
 
5.3%
41
 
5.3%
81
 
5.3%
Other Punctuation
ValueCountFrequency (%)
.5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common24
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
35
20.8%
.5
20.8%
05
20.8%
73
12.5%
92
 
8.3%
21
 
4.2%
61
 
4.2%
41
 
4.2%
81
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
20.8%
.5
20.8%
05
20.8%
73
12.5%
92
 
8.3%
21
 
4.2%
61
 
4.2%
41
 
4.2%
81
 
4.2%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)80.0%
Missing162
Missing (%)97.0%
Memory size1.4 KiB
TV 2
Hunan TV
TV Globo
Disney Channel

Length

Max length14
Median length8
Mean length7.6
Min length4

Characters and Unicode

Total characters38
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st rowTV 2
2nd rowTV 2
3rd rowHunan TV
4th rowTV Globo
5th rowDisney Channel

Common Values

ValueCountFrequency (%)
TV 22
 
1.2%
Hunan TV1
 
0.6%
TV Globo1
 
0.6%
Disney Channel1
 
0.6%
(Missing)162
97.0%

Length

2022-09-04T23:38:01.658652image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:38:01.807050image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
tv4
40.0%
22
20.0%
hunan1
 
10.0%
globo1
 
10.0%
disney1
 
10.0%
channel1
 
10.0%

Most occurring characters

ValueCountFrequency (%)
5
13.2%
n5
13.2%
T4
10.5%
V4
10.5%
a2
 
5.3%
e2
 
5.3%
o2
 
5.3%
l2
 
5.3%
22
 
5.3%
G1
 
2.6%
Other values (9)9
23.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter19
50.0%
Uppercase Letter12
31.6%
Space Separator5
 
13.2%
Decimal Number2
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n5
26.3%
a2
 
10.5%
e2
 
10.5%
o2
 
10.5%
l2
 
10.5%
u1
 
5.3%
b1
 
5.3%
i1
 
5.3%
s1
 
5.3%
y1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
T4
33.3%
V4
33.3%
G1
 
8.3%
H1
 
8.3%
D1
 
8.3%
C1
 
8.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Decimal Number
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin31
81.6%
Common7
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n5
16.1%
T4
12.9%
V4
12.9%
a2
 
6.5%
e2
 
6.5%
o2
 
6.5%
l2
 
6.5%
G1
 
3.2%
u1
 
3.2%
H1
 
3.2%
Other values (7)7
22.6%
Common
ValueCountFrequency (%)
5
71.4%
22
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII38
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
13.2%
n5
13.2%
T4
10.5%
V4
10.5%
a2
 
5.3%
e2
 
5.3%
o2
 
5.3%
l2
 
5.3%
22
 
5.3%
G1
 
2.6%
Other values (9)9
23.7%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)80.0%
Missing162
Missing (%)97.0%
Memory size1.4 KiB
Norway
China
Brazil
United States

Length

Max length13
Median length6
Mean length7.2
Min length5

Characters and Unicode

Total characters36
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st rowNorway
2nd rowNorway
3rd rowChina
4th rowBrazil
5th rowUnited States

Common Values

ValueCountFrequency (%)
Norway2
 
1.2%
China1
 
0.6%
Brazil1
 
0.6%
United States1
 
0.6%
(Missing)162
97.0%

Length

2022-09-04T23:38:01.965167image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:38:02.114476image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
norway2
33.3%
china1
16.7%
brazil1
16.7%
united1
16.7%
states1
16.7%

Most occurring characters

ValueCountFrequency (%)
a5
13.9%
t3
 
8.3%
r3
 
8.3%
i3
 
8.3%
N2
 
5.6%
w2
 
5.6%
y2
 
5.6%
n2
 
5.6%
o2
 
5.6%
e2
 
5.6%
Other values (10)10
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter29
80.6%
Uppercase Letter6
 
16.7%
Space Separator1
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a5
17.2%
t3
10.3%
r3
10.3%
i3
10.3%
w2
 
6.9%
y2
 
6.9%
n2
 
6.9%
o2
 
6.9%
e2
 
6.9%
d1
 
3.4%
Other values (4)4
13.8%
Uppercase Letter
ValueCountFrequency (%)
N2
33.3%
S1
16.7%
B1
16.7%
U1
16.7%
C1
16.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin35
97.2%
Common1
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a5
14.3%
t3
 
8.6%
r3
 
8.6%
i3
 
8.6%
N2
 
5.7%
w2
 
5.7%
y2
 
5.7%
n2
 
5.7%
o2
 
5.7%
e2
 
5.7%
Other values (9)9
25.7%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a5
13.9%
t3
 
8.3%
r3
 
8.3%
i3
 
8.3%
N2
 
5.6%
w2
 
5.6%
y2
 
5.6%
n2
 
5.6%
o2
 
5.6%
e2
 
5.6%
Other values (10)10
27.8%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)80.0%
Missing162
Missing (%)97.0%
Memory size1.4 KiB
NO
CN
BR
US

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st rowNO
2nd rowNO
3rd rowCN
4th rowBR
5th rowUS

Common Values

ValueCountFrequency (%)
NO2
 
1.2%
CN1
 
0.6%
BR1
 
0.6%
US1
 
0.6%
(Missing)162
97.0%

Length

2022-09-04T23:38:02.198514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:38:02.330551image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
no2
40.0%
cn1
20.0%
br1
20.0%
us1
20.0%

Most occurring characters

ValueCountFrequency (%)
N3
30.0%
O2
20.0%
C1
 
10.0%
B1
 
10.0%
R1
 
10.0%
U1
 
10.0%
S1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter10
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N3
30.0%
O2
20.0%
C1
 
10.0%
B1
 
10.0%
R1
 
10.0%
U1
 
10.0%
S1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N3
30.0%
O2
20.0%
C1
 
10.0%
B1
 
10.0%
R1
 
10.0%
U1
 
10.0%
S1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N3
30.0%
O2
20.0%
C1
 
10.0%
B1
 
10.0%
R1
 
10.0%
U1
 
10.0%
S1
 
10.0%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)80.0%
Missing162
Missing (%)97.0%
Memory size1.4 KiB
Europe/Oslo
Asia/Shanghai
America/Noronha
America/New_York

Length

Max length16
Median length15
Mean length13.2
Min length11

Characters and Unicode

Total characters66
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st rowEurope/Oslo
2nd rowEurope/Oslo
3rd rowAsia/Shanghai
4th rowAmerica/Noronha
5th rowAmerica/New_York

Common Values

ValueCountFrequency (%)
Europe/Oslo2
 
1.2%
Asia/Shanghai1
 
0.6%
America/Noronha1
 
0.6%
America/New_York1
 
0.6%
(Missing)162
97.0%

Length

2022-09-04T23:38:02.508779image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:38:02.614783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/oslo2
40.0%
asia/shanghai1
20.0%
america/noronha1
20.0%
america/new_york1
20.0%

Most occurring characters

ValueCountFrequency (%)
o7
 
10.6%
a6
 
9.1%
r6
 
9.1%
e5
 
7.6%
/5
 
7.6%
i4
 
6.1%
h3
 
4.5%
s3
 
4.5%
A3
 
4.5%
N2
 
3.0%
Other values (14)22
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter49
74.2%
Uppercase Letter11
 
16.7%
Other Punctuation5
 
7.6%
Connector Punctuation1
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o7
14.3%
a6
12.2%
r6
12.2%
e5
10.2%
i4
8.2%
h3
 
6.1%
s3
 
6.1%
c2
 
4.1%
m2
 
4.1%
n2
 
4.1%
Other values (6)9
18.4%
Uppercase Letter
ValueCountFrequency (%)
A3
27.3%
N2
18.2%
E2
18.2%
O2
18.2%
S1
 
9.1%
Y1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
/5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin60
90.9%
Common6
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o7
 
11.7%
a6
 
10.0%
r6
 
10.0%
e5
 
8.3%
i4
 
6.7%
h3
 
5.0%
s3
 
5.0%
A3
 
5.0%
N2
 
3.3%
c2
 
3.3%
Other values (12)19
31.7%
Common
ValueCountFrequency (%)
/5
83.3%
_1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o7
 
10.6%
a6
 
9.1%
r6
 
9.1%
e5
 
7.6%
/5
 
7.6%
i4
 
6.1%
h3
 
4.5%
s3
 
4.5%
A3
 
4.5%
N2
 
3.0%
Other values (14)22
33.3%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing167
Missing (%)100.0%
Memory size1.4 KiB

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing167
Missing (%)100.0%
Memory size1.4 KiB

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing167
Missing (%)100.0%
Memory size1.4 KiB

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing166
Missing (%)99.4%
Memory size1.4 KiB
Russian Federation

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRussian Federation

Common Values

ValueCountFrequency (%)
Russian Federation1
 
0.6%
(Missing)166
99.4%

Length

2022-09-04T23:38:02.732789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:38:02.860780image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
russian1
50.0%
federation1
50.0%

Most occurring characters

ValueCountFrequency (%)
s2
11.1%
i2
11.1%
a2
11.1%
n2
11.1%
e2
11.1%
R1
 
5.6%
u1
 
5.6%
1
 
5.6%
F1
 
5.6%
d1
 
5.6%
Other values (3)3
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15
83.3%
Uppercase Letter2
 
11.1%
Space Separator1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s2
13.3%
i2
13.3%
a2
13.3%
n2
13.3%
e2
13.3%
u1
6.7%
d1
6.7%
r1
6.7%
t1
6.7%
o1
6.7%
Uppercase Letter
ValueCountFrequency (%)
R1
50.0%
F1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin17
94.4%
Common1
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s2
11.8%
i2
11.8%
a2
11.8%
n2
11.8%
e2
11.8%
R1
5.9%
u1
5.9%
F1
5.9%
d1
5.9%
r1
5.9%
Other values (2)2
11.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s2
11.1%
i2
11.1%
a2
11.1%
n2
11.1%
e2
11.1%
R1
 
5.6%
u1
 
5.6%
1
 
5.6%
F1
 
5.6%
d1
 
5.6%
Other values (3)3
16.7%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing166
Missing (%)99.4%
Memory size1.4 KiB
RU

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRU

Common Values

ValueCountFrequency (%)
RU1
 
0.6%
(Missing)166
99.4%

Length

2022-09-04T23:38:02.983708image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:38:03.112781image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ru1
100.0%

Most occurring characters

ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R1
50.0%
U1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing166
Missing (%)99.4%
Memory size1.4 KiB
Asia/Kamchatka

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsia/Kamchatka

Common Values

ValueCountFrequency (%)
Asia/Kamchatka1
 
0.6%
(Missing)166
99.4%

Length

2022-09-04T23:38:03.247857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:38:03.360857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka1
100.0%

Most occurring characters

ValueCountFrequency (%)
a4
28.6%
A1
 
7.1%
s1
 
7.1%
i1
 
7.1%
/1
 
7.1%
K1
 
7.1%
m1
 
7.1%
c1
 
7.1%
h1
 
7.1%
t1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter11
78.6%
Uppercase Letter2
 
14.3%
Other Punctuation1
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a4
36.4%
s1
 
9.1%
i1
 
9.1%
m1
 
9.1%
c1
 
9.1%
h1
 
9.1%
t1
 
9.1%
k1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
A1
50.0%
K1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin13
92.9%
Common1
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a4
30.8%
A1
 
7.7%
s1
 
7.7%
i1
 
7.7%
K1
 
7.7%
m1
 
7.7%
c1
 
7.7%
h1
 
7.7%
t1
 
7.7%
k1
 
7.7%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a4
28.6%
A1
 
7.1%
s1
 
7.1%
i1
 
7.1%
/1
 
7.1%
K1
 
7.1%
m1
 
7.1%
c1
 
7.1%
h1
 
7.1%
t1
 
7.1%

Interactions

2022-09-04T23:37:45.714013image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:22.915434image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:25.126602image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:26.931475image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:28.727128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:30.472000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:32.258448image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:33.892219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:35.994454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:37.807505image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:39.616997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:41.923864image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:44.024261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:45.800074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:23.457323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:25.213613image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:27.017470image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:28.850284image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:30.614360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:32.402452image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:34.018224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:36.128679image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:37.904502image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:39.755138image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:42.065857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:44.115201image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:45.912184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:23.614328image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:25.391962image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:27.294469image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:29.006288image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:30.886355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:32.495444image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:34.399880image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:36.251756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:38.166664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:39.867298image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:42.259055image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:44.238792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:46.027260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:23.738580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:25.532307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:27.477552image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:29.132791image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:30.996510image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:32.608784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:34.575420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:36.389684image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:38.266609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:40.026789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:42.418478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:44.399080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:46.189413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:23.918704image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:25.667547image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:27.603139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:29.306727image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:31.150811image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:32.784792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:34.763861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:36.561745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:38.372919image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:40.182865image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:42.846884image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:44.542093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:46.527542image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:24.099501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:25.814764image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:27.695430image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:29.449264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:31.321890image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:32.916794image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:34.873869image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:36.717825image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:38.512523image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:40.356939image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:42.945930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:44.632783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:46.687474image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:24.195641image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:25.984152image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:27.861432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:29.568262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:31.473359image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:33.005784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:34.963860image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:36.866962image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:38.684302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:40.471017image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:43.117342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:44.755789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:46.823043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:24.335645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:26.094365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:28.001587image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:29.689265image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:31.589439image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:33.097791image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:35.060857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:36.961962image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:38.831274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:40.600017image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:43.240687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:44.892788image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:46.955977image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:24.446802image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:26.233571image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:28.107776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:29.817337image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:31.752655image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:33.244783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:35.234184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:37.088047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:38.955532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:40.768432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:43.372777image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:45.007710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:47.030129image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:24.589982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:26.372067image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:28.211778image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:29.913523image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:31.827667image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:33.359785image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:35.384507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:37.212534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:39.089430image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:40.991202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:43.513121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:45.131878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:47.143268image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:24.760161image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:26.496882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:28.339772image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:30.069025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:31.918660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:33.509959image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:35.538660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:37.361841image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:39.220588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:41.305506image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:43.619113image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:45.289141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:47.268555image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:24.896156image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:26.647364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:28.451773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:30.194035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:32.020658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:33.599957image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:35.699761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:37.530428image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:39.339763image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:41.570019image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:43.748886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:45.456459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:47.453555image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:25.024604image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:26.815440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:28.570966image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:30.294078image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:32.142456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:33.731148image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:35.833670image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:37.673501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:39.460226image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:41.745872image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:43.892264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:37:45.587530image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-09-04T23:38:03.448857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-04T23:38:03.890270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-04T23:38:04.292428image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-04T23:38:04.855377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-04T23:37:48.081773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-04T23:37:49.919284image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-04T23:37:50.922141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show._links.nextepisode.hrefimage.mediumimage.original_embedded.show.webChannel.country_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.image_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
01968113https://www.tvmaze.com/episodes/1968113/po-sezonu-videodajdzest-seasonvar-6x50-vypusk-304Выпуск 304650.0regular2020-12-112020-12-11T00:00:00+00:009.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19681137847https://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvarПо сезону. Видеодайджест SeasonvarTalk ShowRussian[]Running9.08.02015-02-13Nonehttp://seasonvar.ru/serial-11488-Po_sezonu_Videodajdzhest_Seasonvar.html[Friday]NaN57NaN56.0SeasonvarRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/294/735323.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/735323.jpg<p>Weekly videodaydzhest on site seasonvar.ru and creative team viruseproject.tv. In ten minutes, we talk about the most important events of the past week: look down on the set is not yet published projects, sharing the secrets of private life actors consider the prospects for the development of genres and discuss news TV industry! In videodaydzheste you will find only reliable information from Russian and foreign publications, as well as take part in choosing the best show of the month! Our weekly news videodaydzhest will suit every viewer, so gather good company with family and friends, as well as stock up on popcorn - these ten minutes you shock, delight and inform the latest news about your favorite TV projects!</p>1662290859https://api.tvmaze.com/shows/7847https://api.tvmaze.com/episodes/2338362https://api.tvmaze.com/episodes/2338363NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11961004https://www.tvmaze.com/episodes/1961004/cuma-2x07-seria-13Серия 1327.0regular2020-12-112020-12-11T00:00:00+00:0022.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196100448402https://www.tvmaze.com/shows/48402/cumaЧума!ScriptedRussian[Comedy]Ended21.021.02020-05-292020-12-18https://www.ivi.ru/watch/chuma-2020[Friday]6.029NaN337.0iviRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/285/713441.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713441.jpg<p><b>Plague</b> – a Comedy project about how hard it is to survive in the middle ages during the plague. This is a story about the residents of the fictional town of Hamburg, locked in a castle under quarantine. Also locked up in the castle is the Messenger William, who, in fact, brought the news of the plague.</p>1609468403https://api.tvmaze.com/shows/48402https://api.tvmaze.com/episodes/1961005NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21976572https://www.tvmaze.com/episodes/1976572/zakon-i-besporyadok-1x05-seria-5Серия 515.0regular2020-12-1112:002020-12-11T00:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197657252118https://www.tvmaze.com/shows/52118/zakon-i-besporyadokZakon i BesporyadokScriptedRussian[Comedy, Action, Crime]Ended30.030.02020-11-272020-12-11https://www.ivi.ru/watch/zakon-i-besporyadok12:00[Friday]NaN4NaN337.0iviRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/285/713460.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713460.jpg<p>Lytk-Angeles, the state of Moskvachussets, has always been a quiet town where every gang had its rightful place. The Colombians smoked plantain, the Irish sipped beer, and the Chinese ate noodles. But one day the evil Russian Communists came and brought sugar with them. They slaughtered all the street vendors of plantain, seized control of the production of matryoshka dolls (a traditional Yugoslav business) and got the whole city hooked on white powder.</p><p>This will be the last case for Eustace Lynch. Famous for his lucky tattoo, an Irish gangster comes to Lytk-Angeles from Dublin (also known as Dubna) to get rid of the Communists. At the same time, Sally Raptor, a police officer from palm beach (also known as Gelendzhik) arrives in the city with a similar task.</p><p>Zakon i Besporyadok is a parody of the films of the 80s and 90s that we watched on videotapes with one-voice voice-over as a child, and a tribute to that forever-gone era when the screen belonged entirely to evil Russians, Asian martial artists and drinking detectives in ridiculous hats. Each episode parodies one of your favorite genres: the characters don't change, but they end up in an Asian fighting game, a crime Thriller, or even a neo-noir story.</p>1616037669https://api.tvmaze.com/shows/52118https://api.tvmaze.com/episodes/1976572NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
31986873https://www.tvmaze.com/episodes/1986873/kotiki-1x10-seria-10Серия 10110.0regular2020-12-112020-12-11T00:00:00+00:0012.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198687352198https://www.tvmaze.com/shows/52198/kotikiКотикиScriptedRussian[Comedy]Ended12.012.02020-11-302020-12-11http://epic-media.ru/project/kotiki10:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN14NaN510.0Epic MediaRussian FederationRUAsia/KamchatkaNoneNaNNaN392682.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpgNone1637555191https://api.tvmaze.com/shows/52198https://api.tvmaze.com/episodes/1986873NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42030151https://www.tvmaze.com/episodes/2030151/fox-spirit-matchmaker-9x01-episode-122Episode 12291.0regular2020-12-112020-12-11T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/203015120734https://www.tvmaze.com/shows/20734/fox-spirit-matchmakerFox Spirit MatchmakerAnimationChinese[Comedy, Anime, Fantasy, Romance]Running10.010.02015-06-26Nonehttp://www.bilibili.com/bangumi/%E7%8B%90%E5%A6%96%E5%B0%8F%E7%BA%A2%E5%A8%98/[Friday]NaN68NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNaNNaN310311.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/73/183375.jpghttps://static.tvmaze.com/uploads/images/original_untouched/73/183375.jpg<p>Buy UCO from childhood grew up in the clan, Ichigo, but their "care" was for him a living Hell. Constant bullying, stealing the Goodies, without which Ycu can not live, and even eternal persecution, from the fair sex turned him into a goner cheapskate who wants to take revenge on his tormentors. But revenge is sweet and the path to it is thorny and to accomplish, UCU need to marry a girl Yes, as soon as possible. But when the heroes just happen? Never! And meeting with the small and the big-eared Fox Susan su su did not just destroy his plans, but starts spinning the wheel of fate that was waiting in the wings for hundreds of years!</p>1629636336https://api.tvmaze.com/shows/20734https://api.tvmaze.com/episodes/2153563NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52030152https://www.tvmaze.com/episodes/2030152/fox-spirit-matchmaker-9x02-episode-123Episode 12392.0regular2020-12-112020-12-11T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/203015220734https://www.tvmaze.com/shows/20734/fox-spirit-matchmakerFox Spirit MatchmakerAnimationChinese[Comedy, Anime, Fantasy, Romance]Running10.010.02015-06-26Nonehttp://www.bilibili.com/bangumi/%E7%8B%90%E5%A6%96%E5%B0%8F%E7%BA%A2%E5%A8%98/[Friday]NaN68NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNaNNaN310311.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/73/183375.jpghttps://static.tvmaze.com/uploads/images/original_untouched/73/183375.jpg<p>Buy UCO from childhood grew up in the clan, Ichigo, but their "care" was for him a living Hell. Constant bullying, stealing the Goodies, without which Ycu can not live, and even eternal persecution, from the fair sex turned him into a goner cheapskate who wants to take revenge on his tormentors. But revenge is sweet and the path to it is thorny and to accomplish, UCU need to marry a girl Yes, as soon as possible. But when the heroes just happen? Never! And meeting with the small and the big-eared Fox Susan su su did not just destroy his plans, but starts spinning the wheel of fate that was waiting in the wings for hundreds of years!</p>1629636336https://api.tvmaze.com/shows/20734https://api.tvmaze.com/episodes/2153563NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
61972563https://www.tvmaze.com/episodes/1972563/the-wolf-1x21-episode-21Episode 21121.0regular2020-12-112020-12-11T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197256347912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese[Drama, Romance, History]Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html[]NaN38NaN118.0YoukuChinaCNAsia/ShanghaiNoneNaNNaN331095.0tt8871128https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpghttps://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1648217029https://api.tvmaze.com/shows/47912https://api.tvmaze.com/episodes/1972591NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71972564https://www.tvmaze.com/episodes/1972564/the-wolf-1x22-episode-22Episode 22122.0regular2020-12-112020-12-11T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197256447912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese[Drama, Romance, History]Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html[]NaN38NaN118.0YoukuChinaCNAsia/ShanghaiNoneNaNNaN331095.0tt8871128https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpghttps://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1648217029https://api.tvmaze.com/shows/47912https://api.tvmaze.com/episodes/1972591NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1582300445https://www.tvmaze.com/episodes/2300445/justimus-esittaa-duo-2x07-samu-kuoleeSamu kuolee27.0regular2020-12-1100:012020-12-11T22:01:00+00:0018.0NaNNoneNaNhttps://api.tvmaze.com/episodes/230044560427https://www.tvmaze.com/shows/60427/justimus-esittaa-duoJustimus esittää: DuoScriptedFinnish[]Ended18.018.02019-11-222020-12-11https://areena.yle.fi/1-5028404100:01[Friday]NaN2NaN220.0Yle AreenaFinlandFIEurope/HelsinkiNoneNaNNaN373187.0tt11321910https://static.tvmaze.com/uploads/images/medium_portrait/395/989194.jpghttps://static.tvmaze.com/uploads/images/original_untouched/395/989194.jpgNone1648054757https://api.tvmaze.com/shows/60427https://api.tvmaze.com/episodes/2300446NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1592300446https://www.tvmaze.com/episodes/2300446/justimus-esittaa-duo-2x08-hesaHesa28.0regular2020-12-1100:012020-12-11T22:01:00+00:0018.0NaNNoneNaNhttps://api.tvmaze.com/episodes/230044660427https://www.tvmaze.com/shows/60427/justimus-esittaa-duoJustimus esittää: DuoScriptedFinnish[]Ended18.018.02019-11-222020-12-11https://areena.yle.fi/1-5028404100:01[Friday]NaN2NaN220.0Yle AreenaFinlandFIEurope/HelsinkiNoneNaNNaN373187.0tt11321910https://static.tvmaze.com/uploads/images/medium_portrait/395/989194.jpghttps://static.tvmaze.com/uploads/images/original_untouched/395/989194.jpgNone1648054757https://api.tvmaze.com/shows/60427https://api.tvmaze.com/episodes/2300446NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1661985051https://www.tvmaze.com/episodes/1985051/the-last-drive-in-with-joe-bob-briggs-9x02-deadly-gamesDeadly Games92.0regular2020-12-1123:002020-12-12T04:00:00+00:00120.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198505145090https://www.tvmaze.com/shows/45090/the-last-drive-in-with-joe-bob-briggsThe Last Drive-In with Joe Bob BriggsVarietyEnglish[Comedy, Fantasy, Horror]Running120.0126.02018-07-13Nonehttps://www.shudder.com/series/watch/the-last-drive-in-with-joe-bob-briggs/4863686[Friday]NaN81NaN213.0ShudderUnited StatesUSAmerica/New_YorkNoneNaNNaN350354.0tt8865058https://static.tvmaze.com/uploads/images/medium_portrait/224/562046.jpghttps://static.tvmaze.com/uploads/images/original_untouched/224/562046.jpg<p>Proving once again that "the drive-in will never die," iconic horror host and exploitation movie aficionado Joe Bob Briggs is back with an all-new Shudder Original series, hosting weekly Friday night double features streaming live exclusively on Shudder. Every week, The Last Drive-In series offers an eclectic pairing of films, with selections ranging across five decades and running the gamut from horror classics to obscurities and foreign cult favorites. And from time to time, special surprise guests will drop in on Joe Bob and Darcy the Mail Girl.</p>1656963699https://api.tvmaze.com/shows/45090https://api.tvmaze.com/episodes/2357129NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN